We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Periodic Labs is building an AI that can simulate science and verify its own predictions — training on the full scientific method. Central to that mission is a high-throughput experimental materials science lab that handles hazardous chemistries, high-pressure and high-temperature processes, air-sensitive synthesis, toxic gas exposure risks, and an expanding suite of thin-film deposition tools including PVD, PLD and the complexity of what we run overnight and autonomously is increasing every month.
We believe EHS is integral to this ambition, not a compliance function bolted on after the fact, but a core design discipline that makes autonomous science possible. This EHS role and the person will build our safety architecture, defining permitting strategy, designing life safety systems, conducting process hazard analyses, and ultimately training our AI to reason about risk during experimental planning and execution.
Own and manage all permitting processes with local, state, and federal agencies: Fire Department/CUPA via Accela, CERS submissions for hazardous materials, AQMD/BAAQMD air permits, and TSDF coordination for hazardous waste.
Maintain and update chemical inventory systems, SDS library, and hazard labeling in compliance with OSHA, CalEPA, and permitted MAQ thresholds including managing the expansion of our chemical inventory as new thin-film processes introduce HF-based wet chemistry, fluoride compounds, and specialty gases.
Lead Hazard Communication (HazCom) and SDS training programs for lab staff, including night shift and autonomous overnight operation protocols.
Coordinate EHS inspections and maintain required documentation and postings across both the existing powder lab and thin-film facility.
Design and review life safety systems, including fire suppression, e-stop networks, gas detection (including toxic gas alarms for HF, H2Se, and other process chemistries), interlocks, alarm interfaces, and emissions/waste abatement systems such as baghouses and scrubbers.
Conduct and document HAZOPs, PHA/FMEA, and risk assessments for new processes and lab systems, including high-pressure furnace operations, glovebox workflows, and thin-film deposition platforms.
Establish operational readiness and laboratory reliability systems for autonomous operations, including pre-startup safety reviews (PSSR), commissioning validation, alarm rationalization, startup/shutdown procedures, and critical equipment inspection programs.
Partner with automation and controls teams to implement machine safeguarding, fail-safes, interlocks, robotics safety controls, functional safety validation, safety PLC reviews, and automated motion hazard assessments for autonomous experimental systems.
Collaborate with ML/AI engineers on training an LLM to reason through process hazards, risk assessments, and safety constraints during experimental planning and autonomous execution — making EHS a first-class input to our AI’s decision-making.
Lead the site EH&S team through a hands-on approach to problem solving and operational support while promoting a strong safety and environmental culture. Ensure compliance with applicable EH&S regulations and standards, develop and improve programs aligned with company goals, and actively partner with lab and operations teams on day-to-day safety challenges. Own the digital EHS infrastructure, integrating inspections, training records, incident reporting, compliance tracking, KPI dashboards, action-item tracking, and audit workflows into a unified operational safety platform.
10+ years of experience in EHS, process safety, or chemical operations in labs, pilot plants, or manufacturing environments preferably in solid-state chemistry, materials science processing, or lab automation.
Strong knowledge of EH&S regulations, standards, and best practices.
Hands-on experience conducting HAZOPs or FMEAs and designing or reviewing functional safety systems.
Certification in EH&S (e.g., Certified Safety Professional, Certified Industrial Hygienist) is a plus.
Comfort working on-site in a fast-paced, high-complexity lab environment where experiments run 24/7 and the hazard profile evolves as new processes and equipment are introduced.
Experience designing EHS systems for autonomous or semi-autonomous lab environments where processes run without continuous human supervision.
Background supporting the build-out of a new laboratory facility, including coordinating permitting and safety system design in parallel with construction.
Familiarity with AI or ML tools as applied to risk assessment, safety documentation, or experimental planning or genuine curiosity about how to apply them.
Active participation in technical committees contributing to OSHA, NFPA, or IEC standard development.
Demonstrated accomplishments recognized in your field.
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $200,000–$250,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best: the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nPeriodic Labs is building an AI that can simulate science and verify its own predictions — training on the full scientific method. Central to that mission is a high-throughput experimental materials science lab that handles hazardous chemistries, high-pressure and high-temperature processes, air-sensitive synthesis, toxic gas exposure risks, and an expanding suite of thin-film deposition tools including PVD, PLD and the complexity of what we run overnight and autonomously is increasing every month.\n\nWe believe EHS is integral to this ambition, not a compliance function bolted on after the fact, but a core design discipline that makes autonomous science possible. This EHS role and the person will build our safety architecture, defining permitting strategy, designing life safety systems, conducting process hazard analyses, and ultimately training our AI to reason about risk during experimental planning and execution.\n\n\n\n\nWHAT YOU’LL DO\n\n - Own and manage all permitting processes with local, state, and federal agencies: Fire Department/CUPA via Accela, CERS submissions for hazardous materials, AQMD/BAAQMD air permits, and TSDF coordination for hazardous waste.\n\n - Maintain and update chemical inventory systems, SDS library, and hazard labeling in compliance with OSHA, CalEPA, and permitted MAQ thresholds including managing the expansion of our chemical inventory as new thin-film processes introduce HF-based wet chemistry, fluoride compounds, and specialty gases.\n\n - Lead Hazard Communication (HazCom) and SDS training programs for lab staff, including night shift and autonomous overnight operation protocols.\n\n - Coordinate EHS inspections and maintain required documentation and postings across both the existing powder lab and thin-film facility.\n\n - Design and review life safety systems, including fire suppression, e-stop networks, gas detection (including toxic gas alarms for HF, H2Se, and other process chemistries), interlocks, alarm interfaces, and emissions/waste abatement systems such as baghouses and scrubbers.\n\n - Conduct and document HAZOPs, PHA/FMEA, and risk assessments for new processes and lab systems, including high-pressure furnace operations, glovebox workflows, and thin-film deposition platforms.\n\n - Establish operational readiness and laboratory reliability systems for autonomous operations, including pre-startup safety reviews (PSSR), commissioning validation, alarm rationalization, startup/shutdown procedures, and critical equipment inspection programs.\n\n - Partner with automation and controls teams to implement machine safeguarding, fail-safes, interlocks, robotics safety controls, functional safety validation, safety PLC reviews, and automated motion hazard assessments for autonomous experimental systems.\n\n - Collaborate with ML/AI engineers on training an LLM to reason through process hazards, risk assessments, and safety constraints during experimental planning and autonomous execution — making EHS a first-class input to our AI’s decision-making.\n\n - Lead the site EH&S team through a hands-on approach to problem solving and operational support while promoting a strong safety and environmental culture. Ensure compliance with applicable EH&S regulations and standards, develop and improve programs aligned with company goals, and actively partner with lab and operations teams on day-to-day safety challenges. Own the digital EHS infrastructure, integrating inspections, training records, incident reporting, compliance tracking, KPI dashboards, action-item tracking, and audit workflows into a unified operational safety platform.\n \n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - 10+ years of experience in EHS, process safety, or chemical operations in labs, pilot plants, or manufacturing environments preferably in solid-state chemistry, materials science processing, or lab automation.\n\n - Strong knowledge of EH&S regulations, standards, and best practices.\n\n - Hands-on experience conducting HAZOPs or FMEAs and designing or reviewing functional safety systems.\n\n - Certification in EH&S (e.g., Certified Safety Professional, Certified Industrial Hygienist) is a plus.\n\n - Comfort working on-site in a fast-paced, high-complexity lab environment where experiments run 24/7 and the hazard profile evolves as new processes and equipment are introduced.\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience designing EHS systems for autonomous or semi-autonomous lab environments where processes run without continuous human supervision.\n\n - Background supporting the build-out of a new laboratory facility, including coordinating permitting and safety system design in parallel with construction.\n\n - Familiarity with AI or ML tools as applied to risk assessment, safety documentation, or experimental planning or genuine curiosity about how to apply them.\n\n - Active participation in technical committees contributing to OSHA, NFPA, or IEC standard development.\n\n - Demonstrated accomplishments recognized in your field.\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\nCompensation: $200,000–$250,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas.\n\n\n\nWe’re building a team of the world’s best: the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.\n\n"},{"id":"e90c6050-e544-4a2b-ae30-7c41e5eb4f16","title":"Research Scientist, Materials Characterization","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-07-09T22:42:04.249+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/e90c6050-e544-4a2b-ae30-7c41e5eb4f16","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/e90c6050-e544-4a2b-ae30-7c41e5eb4f16/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Join a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale. As a Research Scientist within the Periodic Labs experimental effort, you bring AI predictions into reality through physics and measurement science. In this role, you will both develop new material characterization approaches and be part of the team developing autonomous discovery loops.
This is a senior, hands-on role. You will own the design and execution of high-fidelity property measurements, drive the development of high-throughput characterization schemes, and collaborate closely with AI, automation, and materials science teams to build feedback loops that accelerate discovery. You will set the standard for measurement quality and data integrity across the lab.
Develop and perform high-fidelity thermodynamic, transport, and spectroscopic measurements of materials, including electronic, magnetic, and thermal properties
Design and implement rapid property measurement schemes to scale up the material characterization process and feed AI-guided discovery pipelines
In collaboration with the AI team, implement automated data analysis and reasoning pipelines for screened materials; contribute to feedback loop design between measurement and prediction
In collaboration with the engineering team, develop autonomous systems for property characterization leveraging robotics and programmable instrumentation
Evaluate, procure, and commission new instrumentation; develop custom measurement setups where commercial solutions are insufficient
Define and enforce data standards, metadata schemas, and documentation practices to ensure measurement outputs are reproducible and reusable
Uphold and contribute to lab safety standards, particularly around cryogenic systems, high-field magnets, and hazardous materials
PhD in Physics, Materials Science, or related field, with 5+ years of hands-on experience in physical property characterization
Deep, demonstrated expertise in electronic and magnetic property measurements, including resistivity, Hall effect, magnetometry, and heat capacity
Strong background in cryogenic measurements and low-noise techniques, including lock-in methods, shielding/grounding, and precision instrumentation
Strong track record of highly impactful research demonstrated by publications in top-tier journals and/or inventions, and recognized leadership in the field
Proficiency with data analysis (e.g., Python/Jupyter, familiarity with instrument SDKs a plus) and disciplined data management practices
Excellent scientific writing, cross-disciplinary collaboration, and strong ownership of experiment quality
Ability to communicate measurement requirements and findings clearly to AI, engineering, and materials science collaborators
Experience with automation of physical property measurement platforms (e.g., PPMS, MPMS, custom rigs)
Experience with the computational prediction and experimental characterization design loop
Experience with spectroscopic characterization techniques such as ARPES, neutron scattering, or optical spectroscopy
Experience with lab buildout, instrument commissioning, and process safety
Experience handling and managing data at scale, including LIMS or similar data infrastructure
Previous work at national laboratories or large-scale user facilities
Minimum education: Bachelor’s degree or similar experience
Employment type: Full-time, 12-month term
Location: Our lab is located in Menlo Park and we prefer folks to be located in Menlo Park or San Francisco but can be flexible based on role
Compensation: $225,000-325,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nJoin a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale. As a Research Scientist within the Periodic Labs experimental effort, you bring AI predictions into reality through physics and measurement science. In this role, you will both develop new material characterization approaches and be part of the team developing autonomous discovery loops.\n\nThis is a senior, hands-on role. You will own the design and execution of high-fidelity property measurements, drive the development of high-throughput characterization schemes, and collaborate closely with AI, automation, and materials science teams to build feedback loops that accelerate discovery. You will set the standard for measurement quality and data integrity across the lab.\n\n\n\n\nWHAT YOU’LL DO\n\n - Develop and perform high-fidelity thermodynamic, transport, and spectroscopic measurements of materials, including electronic, magnetic, and thermal properties\n\n - Design and implement rapid property measurement schemes to scale up the material characterization process and feed AI-guided discovery pipelines\n\n - In collaboration with the AI team, implement automated data analysis and reasoning pipelines for screened materials; contribute to feedback loop design between measurement and prediction\n\n - In collaboration with the engineering team, develop autonomous systems for property characterization leveraging robotics and programmable instrumentation\n\n - Evaluate, procure, and commission new instrumentation; develop custom measurement setups where commercial solutions are insufficient\n\n - Define and enforce data standards, metadata schemas, and documentation practices to ensure measurement outputs are reproducible and reusable\n\n - Uphold and contribute to lab safety standards, particularly around cryogenic systems, high-field magnets, and hazardous materials\n\n\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - PhD in Physics, Materials Science, or related field, with 5+ years of hands-on experience in physical property characterization\n\n - Deep, demonstrated expertise in electronic and magnetic property measurements, including resistivity, Hall effect, magnetometry, and heat capacity\n\n - Strong background in cryogenic measurements and low-noise techniques, including lock-in methods, shielding/grounding, and precision instrumentation\n\n - Strong track record of highly impactful research demonstrated by publications in top-tier journals and/or inventions, and recognized leadership in the field\n\n - Proficiency with data analysis (e.g., Python/Jupyter, familiarity with instrument SDKs a plus) and disciplined data management practices\n\n - Excellent scientific writing, cross-disciplinary collaboration, and strong ownership of experiment quality\n\n - Ability to communicate measurement requirements and findings clearly to AI, engineering, and materials science collaborators\n\n\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience with automation of physical property measurement platforms (e.g., PPMS, MPMS, custom rigs)\n\n - Experience with the computational prediction and experimental characterization design loop\n\n - Experience with spectroscopic characterization techniques such as ARPES, neutron scattering, or optical spectroscopy\n\n - Experience with lab buildout, instrument commissioning, and process safety\n\n - Experience handling and managing data at scale, including LIMS or similar data infrastructure\n\n - Previous work at national laboratories or large-scale user facilities\n\n\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nEmployment type: Full-time, 12-month term\n\nLocation: Our lab is located in Menlo Park and we prefer folks to be located in Menlo Park or San Francisco but can be flexible based on role\n\nCompensation: $225,000-325,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas.\n\n\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"7f36ea6e-3e67-40df-82c6-5540859a2ac5","title":"Research Scientist, Thin Films","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-07-09T21:28:45.867+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/7f36ea6e-3e67-40df-82c6-5540859a2ac5","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/7f36ea6e-3e67-40df-82c6-5540859a2ac5/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Join a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale.
As a Research Scientist in Thin Film Materials Discovery, you will lead thin-film synthesis efforts using advanced PVD platforms, building the experimental foundation for autonomous discovery loops. You will collaborate with computational and AI scientists, and partner with engineers designing next-generation automated laboratory infrastructure.
Develop synthesis strategies to realize novel thin-film materials predicted by AI
Determine and control crystal structures, defects, microstructures, and properties of previously unrealized compounds
Partner with AI and computation teams to build predictive models of materials growth and properties grounded in physics and chemistry
Work with engineers to design, test, and deploy automated growth and characterization hardware
PhD in chemistry, physics, or materials science, with 5+ years of hands-on experience
Deep expertise with thin-film synthesis methods such as sputtering, PLD, and MBE, with demonstrated experience and creativity across diverse chemistries
Strong skills in structural and chemical characterization, particularly of thin films and materials with structures or compositions never before realized experimentally — including diffraction, microscopy, and spectroscopy
Experience probing the optical, electronic, magnetic, thermal, and/or other properties of thin films
Proven record of collaboration with computational groups, especially for high-throughput materials discovery
Demonstrated commitment to laboratory safety and stewardship, with hands-on experience in hazardous chemistries
Strong track record of highly impactful research demonstrated by publications in top-tier journals and/or inventions, and recognized leadership in the field
Experience working in national user facilities such as synchrotrons or neutron sources
Development of novel synthesis or characterization techniques
Comfort with large experimental datasets and analysis pipelines
Experience with automation and scripting in laboratory environments
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $225,000-325,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nJoin a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale.\n\nAs a Research Scientist in Thin Film Materials Discovery, you will lead thin-film synthesis efforts using advanced PVD platforms, building the experimental foundation for autonomous discovery loops. You will collaborate with computational and AI scientists, and partner with engineers designing next-generation automated laboratory infrastructure.\n\n\n\n\nWHAT YOU’LL DO\n\n - Develop synthesis strategies to realize novel thin-film materials predicted by AI\n\n - Determine and control crystal structures, defects, microstructures, and properties of previously unrealized compounds\n\n - Partner with AI and computation teams to build predictive models of materials growth and properties grounded in physics and chemistry\n\n - Work with engineers to design, test, and deploy automated growth and characterization hardware\n\n\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - PhD in chemistry, physics, or materials science, with 5+ years of hands-on experience\n\n - Deep expertise with thin-film synthesis methods such as sputtering, PLD, and MBE, with demonstrated experience and creativity across diverse chemistries\n\n - Strong skills in structural and chemical characterization, particularly of thin films and materials with structures or compositions never before realized experimentally — including diffraction, microscopy, and spectroscopy\n\n - Experience probing the optical, electronic, magnetic, thermal, and/or other properties of thin films\n\n - Proven record of collaboration with computational groups, especially for high-throughput materials discovery\n\n - Demonstrated commitment to laboratory safety and stewardship, with hands-on experience in hazardous chemistries\n\n - Strong track record of highly impactful research demonstrated by publications in top-tier journals and/or inventions, and recognized leadership in the field\n\n\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience working in national user facilities such as synchrotrons or neutron sources\n\n - Development of novel synthesis or characterization techniques\n\n - Comfort with large experimental datasets and analysis pipelines\n\n - Experience with automation and scripting in laboratory environments\n\n\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\nCompensation: $225,000-325,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas.\n\n\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"67f49f4e-2d0c-49f4-9f4b-15dbc840f8f5","title":"Don't See Your Role? Apply Here!","department":"Business and Operations","team":"Business and Operations","employmentType":"FullTime","location":"Menlo Park, Remote","secondaryLocations":[],"publishedAt":"2026-09-11T01:40:33.872+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"USA","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/67f49f4e-2d0c-49f4-9f4b-15dbc840f8f5","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/67f49f4e-2d0c-49f4-9f4b-15dbc840f8f5/application","descriptionHtml":"About Periodic Labs
We are an AI + physical sciences lab building state of the art models to make novel scientific discoveries. We are well funded and growing rapidly. Team members are owners who identify and solve problems without boundaries or bureaucracy. We eagerly learn new tools and new science to push forward our mission.
About the role
We’re always on the lookout for exceptional people - even if there’s no open role that’s a perfect fit right now.
If you believe your skills and experience align with our mission and you're excited about what we're building, we’d love to hear from you.
","descriptionPlain":"About Periodic Labs\n\nWe are an AI + physical sciences lab building state of the art models to make novel scientific discoveries. We are well funded and growing rapidly. Team members are owners who identify and solve problems without boundaries or bureaucracy. We eagerly learn new tools and new science to push forward our mission.\n\n\n\nAbout the role\n\nWe’re always on the lookout for exceptional people - even if there’s no open role that’s a perfect fit right now.\n\nIf you believe your skills and experience align with our mission and you're excited about what we're building, we’d love to hear from you."},{"id":"01d2c4b2-d848-4426-ad5f-7f1052db3a63","title":"Research Scientist, Condensed Matter Theory","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, London, Remote","secondaryLocations":[],"publishedAt":"2025-11-12T19:12:28.374+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/01d2c4b2-d848-4426-ad5f-7f1052db3a63","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/01d2c4b2-d848-4426-ad5f-7f1052db3a63/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Join a world-class team of scientists and engineers pushing the boundaries of physics research in a groundbreaking lab where AI, theory, and automation unlock discoveries at unprecedented speed and scale.
As a Research Scientist in Condensed Matter Theory, you will use theoretical modeling to connect first-principles calculations and experiments. You will collaborate closely with computational and experimental scientists and ML researchers to develop physical understanding that guides and accelerates the discovery of novel quantum materials.
Develop and apply theoretical models to interpret experimental observations and guide materials discovery efforts
Bridge first-principles calculations (e.g., DFT) and experimental results to build predictive physical understanding
Collaborate with ML researchers to incorporate theoretical insights into machine learning models and inform training data strategies
Work with computational and experimental scientists to design experiments and validate theoretical predictions
Communicate theoretical findings clearly across disciplines and contribute to a shared scientific roadmap
PhD in condensed matter theory, with a focus on quantum materials
Deep expertise in relating theoretical models to real materials and experimental observables
Strong publication record demonstrating impactful, independent research
Ability to collaborate effectively across theory, computation, and experiment
Experience running first-principles calculations such as density functional theory (DFT) on realistic systems
Experience with deep learning methods, including graph neural networks, applied to materials or physics problems
Experience modeling superconductivity and/or magnetism in quantum materials
Familiarity with high-throughput computational workflows or materials databases
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $225,000–$325,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nJoin a world-class team of scientists and engineers pushing the boundaries of physics research in a groundbreaking lab where AI, theory, and automation unlock discoveries at unprecedented speed and scale.\n\nAs a Research Scientist in Condensed Matter Theory, you will use theoretical modeling to connect first-principles calculations and experiments. You will collaborate closely with computational and experimental scientists and ML researchers to develop physical understanding that guides and accelerates the discovery of novel quantum materials.\n\n\n\n\nWHAT YOU’LL DO\n\n - Develop and apply theoretical models to interpret experimental observations and guide materials discovery efforts\n\n - Bridge first-principles calculations (e.g., DFT) and experimental results to build predictive physical understanding\n\n - Collaborate with ML researchers to incorporate theoretical insights into machine learning models and inform training data strategies\n\n - Work with computational and experimental scientists to design experiments and validate theoretical predictions\n\n - Communicate theoretical findings clearly across disciplines and contribute to a shared scientific roadmap\n\n\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - PhD in condensed matter theory, with a focus on quantum materials\n\n - Deep expertise in relating theoretical models to real materials and experimental observables\n\n - Strong publication record demonstrating impactful, independent research\n\n - Ability to collaborate effectively across theory, computation, and experiment\n\n\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience running first-principles calculations such as density functional theory (DFT) on realistic systems\n\n - Experience with deep learning methods, including graph neural networks, applied to materials or physics problems\n\n - Experience modeling superconductivity and/or magnetism in quantum materials\n\n - Familiarity with high-throughput computational workflows or materials databases\n\n\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\nCompensation: $225,000–$325,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas.\n\n\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"d88a6590-a2fa-48c5-86bc-61612b5bb0bc","title":"Product Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2025-11-13T18:05:07.588+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/d88a6590-a2fa-48c5-86bc-61612b5bb0bc","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/d88a6590-a2fa-48c5-86bc-61612b5bb0bc/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
We’re hiring a product engineer to build the agentic software layer between our frontier models, our scientific data, our lab systems, and the scientists using them. You’ll build the environment where materials scientists work alongside AI agents to plan experiments, run analyses, coordinate workflows, and turn results into decisions. The right person for this role is excited to define what the working interface between scientists and AI should actually look like.
You’ll turn cutting-edge models into products that become part of real scientific workflows, both inside Periodic and in customer environments. That means designing interfaces, orchestrating tools and agents, integrating with lab and data systems, and building the feedback loops that improve both product behavior and model performance.
As one of our first product hires, you’ll help define product engineering at Periodic: technically deep, ambitious in scope, and tightly coupled to real scientific work.
Prototype quickly and ship continuously — build high-leverage products that become part of scientists’ daily workflow, then refine them through direct feedback from the lab and from customers
Build agentic products and interfaces on top of our frontier models and scientific data, including copilots, experiment planning systems, workflow automation, operational tools, and new interaction patterns that go beyond chat
Design how scientists direct, supervise, and collaborate with AI agents across experiment planning, execution, analysis, and decision-making
Work closely with model researchers to shape product behavior, evaluation signals, telemetry, and feedback loops that improve both the product experience and the underlying models
Own the product end to end, from data model and backend systems to APIs, user experience, deployment, and observability
Spend time with scientists in the lab, understand where time and attention are being lost, and turn those bottlenecks into products before they are formally requested
Help define the product engineering culture at Periodic, including standards for speed, quality, ambition, and taste
Minimum experience: 5+ years
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $250,000-$350,000 base + equity
Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier but define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nWe’re hiring a product engineer to build the agentic software layer between our frontier models, our scientific data, our lab systems, and the scientists using them. You’ll build the environment where materials scientists work alongside AI agents to plan experiments, run analyses, coordinate workflows, and turn results into decisions. The right person for this role is excited to define what the working interface between scientists and AI should actually look like.\n\nYou’ll turn cutting-edge models into products that become part of real scientific workflows, both inside Periodic and in customer environments. That means designing interfaces, orchestrating tools and agents, integrating with lab and data systems, and building the feedback loops that improve both product behavior and model performance.\n\nAs one of our first product hires, you’ll help define product engineering at Periodic: technically deep, ambitious in scope, and tightly coupled to real scientific work.\n\n\n\n\nWHAT YOU’LL DO\n\n - Prototype quickly and ship continuously — build high-leverage products that become part of scientists’ daily workflow, then refine them through direct feedback from the lab and from customers\n\n - Build agentic products and interfaces on top of our frontier models and scientific data, including copilots, experiment planning systems, workflow automation, operational tools, and new interaction patterns that go beyond chat\n\n - Design how scientists direct, supervise, and collaborate with AI agents across experiment planning, execution, analysis, and decision-making\n\n - Work closely with model researchers to shape product behavior, evaluation signals, telemetry, and feedback loops that improve both the product experience and the underlying models\n\n - Own the product end to end, from data model and backend systems to APIs, user experience, deployment, and observability\n\n - Spend time with scientists in the lab, understand where time and attention are being lost, and turn those bottlenecks into products before they are formally requested\n\n - Help define the product engineering culture at Periodic, including standards for speed, quality, ambition, and taste\n\n\n\n\nMECHANICS\n\nMinimum experience: 5+ years\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA (Soon: San Francisco, too)\n\nCompensation: $250,000-$350,000 base + equity\n\nVisa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier but define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"0d96f03c-8f08-44ae-a7cb-8c4bbc80976c","title":"Computational Scientist, Structural & Thermal","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-07-16T20:08:29.763+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/0d96f03c-8f08-44ae-a7cb-8c4bbc80976c","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/0d96f03c-8f08-44ae-a7cb-8c4bbc80976c/application","descriptionHtml":"Periodic Labs is an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, semiconductors, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Periodic Labs is building AI systems that can simulate physical science, verify predictions, and train on the full scientific method. We are looking for a Computational Scientist to develop structural, thermal, and coupled thermo-mechanical simulation capabilities for semiconductor systems and advanced materials.
This role is for someone who thinks of themselves as both a scientist and a software engineer. You understand solid mechanics and heat transfer at a level that goes beyond configuring a commercial FEA package, and you are comfortable building, extending, or automating solvers when the physics or scale of the problem requires it.
Develop agent-based structural and thermal simulation capabilities for semiconductor systems, including wafer stress and warpage, thin-film residual stress, thermo-mechanical reliability, thermal budget modeling, process-induced deformation, fracture and delamination, and coupled heat-stress problems.
Build or extend custom solvers where commercial FEA tools are too slow, too opaque, or insufficiently flexible. This may include custom FEM implementations, phase-field fracture models, crystal plasticity codes, thin-film mechanics frameworks, or reduced-order mechanical models, written in Python, C++, or Julia.
Model materials behavior at the level the physics requires: elasticity, plasticity, viscoelasticity, creep, fracture, diffusion-induced stress, thermal expansion mismatch, interfacial mechanics, and materials evolution under process conditions.
Validate models against experimental measurements including wafer metrology, curvature and bow measurements, DIC, profilometry, nanoindentation, or failure analysis data.
Design and curate evaluation datasets in collaboration with RL researchers to train LLMs capable of directing complex simulation pipelines.
Generate simulated datasets for ML training in regimes where experimental coverage is expensive or difficult to achieve.
Build and automate simulation pipelines at scale, architecting workflows that connect simulation outputs to data infrastructure, ML systems, and autonomous experimentation loops.
Periodic Labs is an early-stage startup, and we're looking for someone who can bring technical leadership to modeling structural and thermal behavior in semiconductor devices, not necessarily someone who already has every skill listed below. A strong growth mindset, demonstrated ownership, and a track record of getting up to speed quickly in new technical areas are much more important than experience in semiconductors.
A PhD or equivalent research experience in mechanical engineering, materials science, aerospace engineering, or a closely related field, with a strong foundation in solid mechanics and heat transfer. Early-career candidates with strong research or engineering output are encouraged to apply.
Hands-on experience with computational mechanics at the code level: writing or substantially modifying FEM codes, implementing constitutive models, or developing custom solvers for structural or thermal problems.
Familiarity with open-source simulation frameworks such as FEniCS, deal.II, MOOSE, or similar is a strong positive signal. Contributions to open-source projects that others actually use are even better.
Strong Python skills, with C++, Julia, or Fortran proficiency a plus. Experience running simulations programmatically at scale rather than through point-and-click tools.
Deep understanding of solid mechanics theory: continuum mechanics, tensor formulations, constitutive modeling, variational methods, and numerical methods for PDEs.
Experience using mechanics or thermal simulations to explain experimental observations, guide materials or process decisions, or surface failure mechanisms that were not obvious from measurement alone.
Genuine curiosity about AI and a desire to work at the boundary of simulation and machine learning.
Experience with GPU-accelerated FEM, reduced-order mechanical models, surrogate models, or physics-informed neural networks for structural problems.
Familiarity with multiscale mechanics: bridging from atomistic or DFT-informed potentials through molecular dynamics, mesoscale methods, and continuum mechanics.
Deep expertise in thin-film mechanics: residual stress, Stoney equation regimes and their limits, film-substrate interactions, delamination, and stress evolution during deposition.
Experience with wafer-scale mechanics: bow, warp, thermal cycling reliability, packaging-induced stress, or interconnect mechanics in advanced packaging contexts.
Background in fracture mechanics or damage modeling: LEFM, cohesive zone models, phase-field fracture, fatigue, or statistical failure models.
Knowledge of semiconductor metrology, failure analysis, or process integration that gives physical intuition for how models connect to real manufacturing decisions.
Minimum education: Bachelor's degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $250,000-350,000 + equity
Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Periodic Labs is seeking a hands-on, detail-oriented Lab Technician to support the daily operations of our high-throughput materials experimentation facility. You’ll work directly alongside our scientists and engineers to keep the lab running at the pace our science demands — performing calibrations, executing QC protocols, supporting method development, and helping build the SOPs and systems that make rigorous, reproducible research possible.
This role is for someone with a science or engineering background who enjoys working with instruments, takes pride in precision and consistency, and is always looking for ways to make workflows faster and more reliable. You’re equally comfortable performing careful manual tasks and thinking critically about how to automate or optimize them over time.
Perform regular calibration and verification of instruments and sensors, maintaining accurate records and flagging drift or anomalies
Execute and continuously refine QC workflows to ensure data integrity across experimental runs
Perform and optimize manual material handling and preparation steps — including weighing, labeling, packaging, and batch preparation — with an eye toward efficiency and automation
Assist with inventory tracking, chemical management, and lab organization; keep shared spaces clean, stocked, and functional
Collaborate with scientists and engineers to develop, document, and iterate on SOPs for routine lab procedures
Identify inefficiencies in manual workflows and proactively propose or implement improvements
Support the onboarding and training of new technicians on lab best practices, equipment operation, and safety protocols
Assist with the development of QC and metrology protocols for new processes and instruments as our capabilities expand
Participate in test runs and validation of new labware, equipment, or experimental methods
Troubleshoot equipment and process anomalies; escalate appropriately and document findings clearly
A bachelor’s degree in chemistry, materials science, mechanical or chemical engineering, or a related field — or equivalent hands-on experience in a technical lab setting
A demonstrated ability to follow detailed SOPs with precision and maintain high standards of consistency and cleanliness
Comfort performing physical, repetitive tasks carefully — and the motivation to make them more efficient over time
Technical curiosity and eagerness to learn how to operate, maintain, and improve complex equipment
A no-task-too-small attitude: moving materials, cleaning tools, and prepping batches are part of the daily rhythm and you do them with care
Strong written and verbal communication — you document clearly, flag problems early, and collaborate well across technical and non-technical teammates
Comfort with basic software tools such as Excel, Google Sheets, or lab inventory systems
Experience in a robotics-integrated lab, pilot plant, or high-throughput R&D environment
Familiarity with LIMS, LES, MES, SCADA, or other lab data and process control systems
Prior work in cleanroom, semiconductor, battery, or analytical chemistry settings
Experience with powered machinery and tools such as pallet jacks, impact wrenches, or similar equipment
Background in one or more characterization techniques — XRD, SEM/EDS, TGA/DSC, BET, or metrology tools
Minimum education: Bachelor’s degree or an equivalent combination of education and training or experience
Location: Our lab is located in Menlo Park
Compensation: The annual compensation range for this role - $100,000-$130,000
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nPeriodic Labs is seeking a hands-on, detail-oriented Lab Technician to support the daily operations of our high-throughput materials experimentation facility. You’ll work directly alongside our scientists and engineers to keep the lab running at the pace our science demands — performing calibrations, executing QC protocols, supporting method development, and helping build the SOPs and systems that make rigorous, reproducible research possible.\n\nThis role is for someone with a science or engineering background who enjoys working with instruments, takes pride in precision and consistency, and is always looking for ways to make workflows faster and more reliable. You’re equally comfortable performing careful manual tasks and thinking critically about how to automate or optimize them over time.\n\n\n\n\nWHAT YOU’LL DO\n\n - Perform regular calibration and verification of instruments and sensors, maintaining accurate records and flagging drift or anomalies\n\n - Execute and continuously refine QC workflows to ensure data integrity across experimental runs\n\n - Perform and optimize manual material handling and preparation steps — including weighing, labeling, packaging, and batch preparation — with an eye toward efficiency and automation\n\n - Assist with inventory tracking, chemical management, and lab organization; keep shared spaces clean, stocked, and functional\n\n - Collaborate with scientists and engineers to develop, document, and iterate on SOPs for routine lab procedures\n\n - Identify inefficiencies in manual workflows and proactively propose or implement improvements\n\n - Support the onboarding and training of new technicians on lab best practices, equipment operation, and safety protocols\n\n - Assist with the development of QC and metrology protocols for new processes and instruments as our capabilities expand\n\n - Participate in test runs and validation of new labware, equipment, or experimental methods\n\n - Troubleshoot equipment and process anomalies; escalate appropriately and document findings clearly\n\n\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - A bachelor’s degree in chemistry, materials science, mechanical or chemical engineering, or a related field — or equivalent hands-on experience in a technical lab setting\n\n - A demonstrated ability to follow detailed SOPs with precision and maintain high standards of consistency and cleanliness\n\n - Comfort performing physical, repetitive tasks carefully — and the motivation to make them more efficient over time\n\n - Technical curiosity and eagerness to learn how to operate, maintain, and improve complex equipment\n\n - A no-task-too-small attitude: moving materials, cleaning tools, and prepping batches are part of the daily rhythm and you do them with care\n\n - Strong written and verbal communication — you document clearly, flag problems early, and collaborate well across technical and non-technical teammates\n\n - Comfort with basic software tools such as Excel, Google Sheets, or lab inventory systems\n\n\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience in a robotics-integrated lab, pilot plant, or high-throughput R&D environment\n\n - Familiarity with LIMS, LES, MES, SCADA, or other lab data and process control systems\n\n - Prior work in cleanroom, semiconductor, battery, or analytical chemistry settings\n\n - Experience with powered machinery and tools such as pallet jacks, impact wrenches, or similar equipment\n\n - Background in one or more characterization techniques — XRD, SEM/EDS, TGA/DSC, BET, or metrology tools\n\n\n\n\nMECHANICS\n\n - Minimum education: Bachelor’s degree or an equivalent combination of education and training or experience\n\n - Location: Our lab is located in Menlo Park\n\n - Compensation: The annual compensation range for this role - $100,000-$130,000\n \n \n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"fd89f03f-545f-4ffb-a051-8581a3ec686a","title":"Business Operations, Product & Science","department":"Business and Operations","team":"Business and Operations","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-08-18T20:20:26.241+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/fd89f03f-545f-4ffb-a051-8581a3ec686a","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/fd89f03f-545f-4ffb-a051-8581a3ec686a/application","descriptionHtml":"About Periodic Labs
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
About the Role
Periodic Labs sits at the intersection of frontier AI and physical science — and the operational challenges we face reflect that complexity. As Business Operations, you will be the connective tissue between our research teams, our model development roadmap, and the broader strategic and operational needs of the company. You will work cross functionally to accelerate the translation of scientific progress into outcomes that matter.
This is a high-ownership role for someone who can operate in deeply technical environments without being a researcher themselves — someone who understands how science gets done, how AI models get built, and what it takes to build the organizational systems that allow both to happen faster. You will help with product-science coordination, and serve as a trusted strategic partner to leadership on the decisions that shape our trajectory.
The ideal candidate has a graduate-level scientific background — physics, chemistry, materials science, or a closely related field — combined with meaningful experience in strategy, operations, or product roles at a technology or research organization. You think rigorously, communicate exceptionally, and have a rare ability to earn the trust of both scientists and executives.
What You’ll Do
Support the operating rhythm of the research organization — research planning cycles, milestone tracking, experiment prioritization, and cross-team coordination between AI and physical sciences
Design and maintain systems that give leadership real-time visibility into research progress, resource utilization, and emerging risks across the model development and lab science roadmaps
Partner with the Head of Research and Principal Scientists to translate long-horizon scientific goals into quarterly operating plans, resourcing decisions, and hiring priorities
Identify and remove the organizational, process, and tooling bottlenecks that slow down researchers and scientists — acting as a force multiplier for the people doing the core work
Coordinate compute, lab equipment, and infrastructure resource allocation across research projects, working closely with infra and lab operations leads
Serve as the operational link between research outputs and product development — ensuring scientific milestones translate into clear product implications and that product needs are legible to research teams
Drive the product planning process in close partnership with founders and product leads: roadmap development, prioritization frameworks, and cross-functional alignment
Build the processes and artifacts (roadmaps, decision logs, spec templates, review cadences) that make the product-science collaboration scalable as we grow
Lead or support evaluation design, benchmark development, and model assessment processes that connect scientific capability to real-world product requirements
Lead special projects and strategic analyses that don’t fit neatly into any existing function: competitive landscape assessments, build/buy/partner decisions, new capability evaluations
Support external partnerships, collaborations, and customer engagements that sit at the boundary of research and commercial — from scoping to execution
You Will Thrive in This Role If You Have
An undergraduate or graduate degree in physics, chemistry, materials science, computational science, or a closely related quantitative discipline — or equivalent depth demonstrated through research or industry experience
4+ years of experience in strategy, operations, product management, chief-of-staff, or a closely related function — with at least some of that time spent inside a technical, research-driven, or AI organization
A genuine ability to read and engage with primary scientific literature, follow technical discussions at the frontier of AI and physical science, and translate what you learn into operational decisions
Exceptional analytical and structured thinking — you can decompose hard problems, build models under uncertainty, and present findings with conviction and intellectual honesty
Outstanding communication skills: you write with precision and clarity, and you can adapt your register from a conversation with a principal scientist to a board presentation without losing rigor
High agency, strong judgment, and the organizational credibility to influence without authority across a team of world-class researchers and engineers
Experience designing and operating planning and prioritization systems in environments where the work is exploratory, the outputs are uncertain, and the stakes are high
A genuine belief in the mission — you are drawn to the idea of using AI to accelerate scientific discovery, and that orientation shapes how you approach your work
Especially Strong Candidates May Also Have
A PhD in a physical science or engineering discipline with research experience at the boundary of computation and experiment — molecular simulation, condensed matter, materials informatics, or similar
Prior experience in a research operations, technical program management, or science strategy role at an AI lab, national lab, or research-intensive technology company
Hands-on experience with AI/ML workflows, model evaluation, or the product development lifecycle for AI-powered applications
A background that spans both the scientific and commercial sides of a technology organization — you’ve sat in rooms with researchers and with customers, and you know how to bridge those worlds
Experience building or scaling operational functions from scratch, including hiring, process design, and tooling selection
Mechanics
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $250,000-$300,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"About Periodic Labs\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\nAbout the Role\n\nPeriodic Labs sits at the intersection of frontier AI and physical science — and the operational challenges we face reflect that complexity. As Business Operations, you will be the connective tissue between our research teams, our model development roadmap, and the broader strategic and operational needs of the company. You will work cross functionally to accelerate the translation of scientific progress into outcomes that matter.\n\nThis is a high-ownership role for someone who can operate in deeply technical environments without being a researcher themselves — someone who understands how science gets done, how AI models get built, and what it takes to build the organizational systems that allow both to happen faster. You will help with product-science coordination, and serve as a trusted strategic partner to leadership on the decisions that shape our trajectory.\n\nThe ideal candidate has a graduate-level scientific background — physics, chemistry, materials science, or a closely related field — combined with meaningful experience in strategy, operations, or product roles at a technology or research organization. You think rigorously, communicate exceptionally, and have a rare ability to earn the trust of both scientists and executives.\n\nWhat You’ll Do\n\n - Support the operating rhythm of the research organization — research planning cycles, milestone tracking, experiment prioritization, and cross-team coordination between AI and physical sciences\n\n - Design and maintain systems that give leadership real-time visibility into research progress, resource utilization, and emerging risks across the model development and lab science roadmaps\n\n - Partner with the Head of Research and Principal Scientists to translate long-horizon scientific goals into quarterly operating plans, resourcing decisions, and hiring priorities\n\n - Identify and remove the organizational, process, and tooling bottlenecks that slow down researchers and scientists — acting as a force multiplier for the people doing the core work\n\n - Coordinate compute, lab equipment, and infrastructure resource allocation across research projects, working closely with infra and lab operations leads\n\n - Serve as the operational link between research outputs and product development — ensuring scientific milestones translate into clear product implications and that product needs are legible to research teams\n\n - Drive the product planning process in close partnership with founders and product leads: roadmap development, prioritization frameworks, and cross-functional alignment\n\n - Build the processes and artifacts (roadmaps, decision logs, spec templates, review cadences) that make the product-science collaboration scalable as we grow\n\n - Lead or support evaluation design, benchmark development, and model assessment processes that connect scientific capability to real-world product requirements\n\n - Lead special projects and strategic analyses that don’t fit neatly into any existing function: competitive landscape assessments, build/buy/partner decisions, new capability evaluations\n\n - Support external partnerships, collaborations, and customer engagements that sit at the boundary of research and commercial — from scoping to execution\n\nYou Will Thrive in This Role If You Have\n\n - An undergraduate or graduate degree in physics, chemistry, materials science, computational science, or a closely related quantitative discipline — or equivalent depth demonstrated through research or industry experience\n\n - 4+ years of experience in strategy, operations, product management, chief-of-staff, or a closely related function — with at least some of that time spent inside a technical, research-driven, or AI organization\n\n - A genuine ability to read and engage with primary scientific literature, follow technical discussions at the frontier of AI and physical science, and translate what you learn into operational decisions\n\n - Exceptional analytical and structured thinking — you can decompose hard problems, build models under uncertainty, and present findings with conviction and intellectual honesty\n\n - Outstanding communication skills: you write with precision and clarity, and you can adapt your register from a conversation with a principal scientist to a board presentation without losing rigor\n\n - High agency, strong judgment, and the organizational credibility to influence without authority across a team of world-class researchers and engineers\n\n - Experience designing and operating planning and prioritization systems in environments where the work is exploratory, the outputs are uncertain, and the stakes are high\n\n - A genuine belief in the mission — you are drawn to the idea of using AI to accelerate scientific discovery, and that orientation shapes how you approach your work\n\nEspecially Strong Candidates May Also Have\n\n - A PhD in a physical science or engineering discipline with research experience at the boundary of computation and experiment — molecular simulation, condensed matter, materials informatics, or similar\n\n - Prior experience in a research operations, technical program management, or science strategy role at an AI lab, national lab, or research-intensive technology company\n\n - Hands-on experience with AI/ML workflows, model evaluation, or the product development lifecycle for AI-powered applications\n\n - A background that spans both the scientific and commercial sides of a technology organization — you’ve sat in rooms with researchers and with customers, and you know how to bridge those worlds\n\n - Experience building or scaling operational functions from scratch, including hiring, process design, and tooling selection\n\nMechanics\n\n - Minimum education: Bachelor’s degree or similar experience\n\n - Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\n - Compensation: $250,000-$300,000 + equity\n\n - Visa sponsorship: Yes, we sponsor visas.\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.\n\n"},{"id":"c398af52-085d-427c-8c0f-8537cfd96ff3","title":"Head of People ","department":"Business and Operations","team":"Business and Operations","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-09-11T01:37:14.778+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/c398af52-085d-427c-8c0f-8537cfd96ff3","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/c398af52-085d-427c-8c0f-8537cfd96ff3/application","descriptionHtml":"About Periodic Labs
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
About the Role
Periodic Labs is growing fast, and we're building the people infrastructure to match. As our Head of People, you'll run the full people function and partner directly with the leadership team to build the organization that will define the next era of AI-driven scientific discovery. You'll design the systems, shape the culture, and lead the people and talent functions that make Periodic Labs a place where exceptional people do the best work of their lives.
This isn't a traditional HR leadership role. We need someone who has operated inside engineering-forward organizations, ideally in frontier AI, physical products, semiconductors, or hardware-forward startups, and who deeply understands how technical teams operate under pressure. You'll be a trusted advisor to founders and senior leaders, bringing both strategic vision and operational rigor.
What You'll Do
Run all things people related, spanning talent, HR business partnering, onboarding, performance, compensation, learning and development.
Lead and scale talent acquisition, including building the recruiting team, evolving hiring processes and infrastructure, and shaping the company’s hiring strategy as it grows.
Partner directly with the leadership team on organizational design, workforce planning, and growth strategy as the company grows through its next phase
Lead employee relations work with professionalism and sound judgment, handling sensitive situations, investigations, and executive coaching with discretion and care
Design the people systems that help our scientific and engineering teams grow, get recognized, and get paid fairly, built for how technical people actually work, not borrowed from a playbook.
Design onboarding programs that integrate new engineers and scientists quickly into the Periodic Labs culture and way of working
Shape how we scale as an organization. This isn't a traditional hierarchy-building exercise, it's figuring out how a lab-first company adds people and structure without losing what makes it work.
Use people data and analytics to surface insights and drive evidence-based decisions on headcount, attrition, engagement, and team effectiveness
You Will Thrive in This Role If You Have
15+ years of HR experience, with meaningful time in a senior people leadership role at a technology, research, or engineering-forward company
Experience building and leading a talent acquisition function, including hiring and managing recruiters, as the company scales
A background supporting teams in physical products, semiconductors, manufacturing, or hardware-forward startups. You understand the operational rhythms and talent profiles of these environments
Experience navigating the intersection of research and engineering cultures, where intellectual rigor, speed, and hands-on problem-solving coexist
Strong command of the full HR spectrum: performance management, compensation design, employee relations, organizational design, and people operations
A builder's mindset. You're comfortable in ambiguous environments where people programs are still being defined and you'll often have to create the playbook from scratch
High EQ and communication skills. You build trust quickly with engineers and scientists, and you know how to navigate difficult conversations with directness and care
Sound judgment on sensitive matters. You handle employee relations and investigations with appropriate seriousness and discretion
Data fluency: you use people analytics to diagnose issues, identify trends, and support decisions with evidence
Especially Strong Candidates May Also Have
Experience at an AI lab, deep tech company, or research institution where the talent profile is unusually specialized
Familiarity with compensation design for rare technical roles, such as physicists, materials scientists, and ML researchers, where standard benchmarks don't apply
Experience scaling an HR function through a growth financing event or rapid headcount expansion
A background in operations, finance, or program management that brings additional analytical depth to the people function
Direct experience owning technical hiring strategy, including sourcing for niche scientific or engineering disciplines
Mechanics
Minimum education: Bachelor's degree or similar experience
Location: Menlo Park, CA
Compensation: $350,000-$450,000 + equity
Visa sponsorship: Yes, we sponsor visas
Periodic Labs is building AI systems that can simulate physical science, verify predictions, and train on the full scientific method. We are looking for a Computational Scientist to build differentiable, accelerator-ready simulations for industrially relevant continuum-physics problems.
You should be equally comfortable with governing equations, solver code, and deep learning. We are open to expertise in any area of continuum-physics, with at least some experience in fluid dynamics. You will work on building simulation capabilities in challenging, data-limited domains requiring a mix of physics-based and empirical approaches.
Build and extend differentiable solvers for continuum simulation (including but not limited to fluid dynamics), especially multi-scale and multi-physics problems.
Implement numerical methods from equations and papers, and diagnose convergence, stability, and modeling failures.
Combine simulation with deep learning for surrogate modeling, learned physics, inverse problems, parameter estimation, and optimization.
Use automatic differentiation and modern accelerators with JAX or PyTorch to make simulations scalable and trainable.
Validate models against experiments, trusted benchmarks, or high-fidelity simulations.
Create datasets and evaluations to guide the development of LLMs to accelerate and automate these tasks.
A PhD or equivalent research experience in applied mathematics, computational science, physics, engineering, computer science, or a related field.
Code-level experience building or substantially modifying PDE solvers, numerical methods, or differentiable simulations.
Deep expertise in at least one continuum domain, with breadth across domains or a demonstrated ability to learn new physics quickly.
Meaningful experience building, training, and evaluating deep-learning models for physical systems.
Strong Python and software-engineering skills, especially JAX, PyTorch, Julia, or C++.
Experience applying simulation to realistic scientific or engineering problems, not only clean academic benchmarks.
A startup mentality: ownership, good judgment under uncertainty, and enthusiasm for building from scratch.
Experience with fluid dynamics plus another continuum domain, or with multiphysics and multiscale modeling.
Expertise in adjoint methods, implicit differentiation, differentiable programming, or scientific optimization.
Experience accelerating scientific software on GPUs or TPUs.
Contributions to scientific open-source software used by others.
Experience connecting simulation to experiments, engineering decisions, semiconductors, or autonomous workflows.
Minimum education: Bachelor's degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $250,000-350,000 + equity
Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
We’re hiring software engineers to build the backend and distributed systems that form the software backbone of an AI-native physical science lab. These systems turn scientific intent into reliable execution: scheduling large simulation workloads, orchestrating experiments and shared equipment, and connecting instruments and automation to the rest of our software.
Depending on your background and interests, you may work across simulation infrastructure, lab orchestration, or automation systems. You do not need prior experience in every area. We care most about strong engineers who can reason about complex systems, make failure visible, and build software that remains reliable as scientific work scales.
You’ll work directly with scientists, infrastructure engineers, and lab engineers to understand how research gets done, then turn prototypes and manual workflows into robust systems without slowing down discovery.
Design and build backend and distributed systems that execute scientific work reliably.
Build scheduling and orchestration for long-running workflows across compute clusters, instruments, and other shared resources.
Create clear APIs, data models, and service boundaries connecting research software, lab information systems, instruments, and automation.
Make execution inspectable and recoverable through durable state, retries, failure handling, observability, and provenance.
Turn promising research prototypes and scientific workflows into maintainable production systems.
Diagnose bottlenecks and failures across application code, infrastructure, data, and hardware integrations.
Work closely with scientists and engineers to improve experimental throughput, reliability, and reproducibility.
Strong software engineering fundamentals and a track record of building production backend or distributed systems.
Experience with asynchronous or long-running work, such as batch jobs, workflow orchestration, data pipelines, schedulers, or shared-resource systems.
The ability to reason clearly about concurrency, idempotency, partial failures, consistency, and resource contention.
Experience designing maintainable APIs and data models for complex systems.
Strong debugging skills across services, infrastructure, dependencies, and data.
Comfort working with technical collaborators to turn ambiguous needs into reliable systems.
You do not need experience in every area below. Depth in one or more may help us identify where you can have the greatest impact.
Large-scale batch or distributed compute, scientific simulation, GPU workloads, or ML infrastructure.
Workflow engines, DAG orchestration, job schedulers, or cluster execution systems.
LIMS, MES, ERP, process-control systems, lab informatics, or scientific data management.
Robotics, hardware controls, instrument drivers, vendor APIs or SDKs, or industrial automation.
Experience in a physical lab, manufacturing environment, or materials-science setting.
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $250,000-350,000 + equity
Visa sponsorship: Yes, we sponsor visas.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nWe’re hiring software engineers to build the backend and distributed systems that form the software backbone of an AI-native physical science lab. These systems turn scientific intent into reliable execution: scheduling large simulation workloads, orchestrating experiments and shared equipment, and connecting instruments and automation to the rest of our software.\nDepending on your background and interests, you may work across simulation infrastructure, lab orchestration, or automation systems. You do not need prior experience in every area. We care most about strong engineers who can reason about complex systems, make failure visible, and build software that remains reliable as scientific work scales.\nYou’ll work directly with scientists, infrastructure engineers, and lab engineers to understand how research gets done, then turn prototypes and manual workflows into robust systems without slowing down discovery.\n\n\n\n\nWHAT YOU’LL DO\n\n - Design and build backend and distributed systems that execute scientific work reliably.\n\n - Build scheduling and orchestration for long-running workflows across compute clusters, instruments, and other shared resources.\n\n - Create clear APIs, data models, and service boundaries connecting research software, lab information systems, instruments, and automation.\n\n - Make execution inspectable and recoverable through durable state, retries, failure handling, observability, and provenance.\n\n - Turn promising research prototypes and scientific workflows into maintainable production systems.\n\n - Diagnose bottlenecks and failures across application code, infrastructure, data, and hardware integrations.\n\n - Work closely with scientists and engineers to improve experimental throughput, reliability, and reproducibility.\n \n \n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE EXPERIENCE WITH\n\n - Strong software engineering fundamentals and a track record of building production backend or distributed systems.\n\n - Experience with asynchronous or long-running work, such as batch jobs, workflow orchestration, data pipelines, schedulers, or shared-resource systems.\n\n - The ability to reason clearly about concurrency, idempotency, partial failures, consistency, and resource contention.\n\n - Experience designing maintainable APIs and data models for complex systems.\n\n - Strong debugging skills across services, infrastructure, dependencies, and data.\n\n - Comfort working with technical collaborators to turn ambiguous needs into reliable systems.\n \n \n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\nYou do not need experience in every area below. Depth in one or more may help us identify where you can have the greatest impact.\n\n - Large-scale batch or distributed compute, scientific simulation, GPU workloads, or ML infrastructure.\n\n - Workflow engines, DAG orchestration, job schedulers, or cluster execution systems.\n\n - LIMS, MES, ERP, process-control systems, lab informatics, or scientific data management.\n\n - Robotics, hardware controls, instrument drivers, vendor APIs or SDKs, or industrial automation.\n\n - Experience in a physical lab, manufacturing environment, or materials-science setting.\n\n\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\nCompensation: $250,000-350,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas."},{"id":"98837207-657f-4116-a112-d8dc6184b49e","title":"Research Associate, Thin Films ","department":"Science","team":"Science","employmentType":"Contract","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-03-10T17:21:15.414+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/98837207-657f-4116-a112-d8dc6184b49e","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/98837207-657f-4116-a112-d8dc6184b49e/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Join our world-class team of scientists and engineers building a lab where AI and automation speed up physical R&D.
Periodic Labs is developing AI that can both simulate science and verify its predictions to train on the full scientific method. A key challenge is the gap between bulk materials discovery and thin-film form: materials our AI predicts and our powder lab synthesizes must ultimately be validated as scalable thin films to be relevant to semiconductor, memory, and advanced materials applications. We are building a dedicated thin-film lab while generating early data at partner facilities.
We're looking for a hands-on Research Associate in Thin Films to run advanced deposition and nanofabrication processes, generate high-quality experimental data, and collaborate closely with our AI and materials teams. This is a 12-month fixed-term position with the potential to convert to full time.
In the near term you will operate at external partner facilities before Periodic’s own tools come online. As the in-house lab is commissioned, you will transition to running experiments on deposition and metrology suite.
As a process module owner, you will execute thin-film deposition and related nanofabrication processes.
Prepare substrates, manage process flows, and maintain detailed experimental records that meet the metadata and data quality standards for AI training. Every experiment you run is a potential data point for our models - documentation quality matters as much as deposition quality.
Perform structural and functional thin-film characterization: XRD/XRR for structure and thickness, ellipsometry and profilometry for film properties, SEM/EDX for morphology and composition, and 4-point probe and basic transport measurements for electrical properties.
Monitor in-situ metrology during deposition to ensure high quality film growth.
Collaborate with the AI and materials science teams to help define which deposition parameters to vary, interpreting film characterization results in context of what the AI predicts, and flagging discrepancies that may indicate new physics or synthesis insights.
Troubleshoot process issues and iterate quickly on recipes under guidance from senior team members. Escalate anomalies rather than work around them, and document both failures and fixes in a format that preserves institutional knowledge.
Currently pursuing or recently completed a PhD (or advanced graduate degree) in materials science, physics, chemistry, or a related field.
Hands-on experience operating thin-film deposition equipment - sputtering, evaporation, PLD, ALD, CVD, MBE, or related techniques - developed in a university or research lab environment.
Familiarity with the practical realities of these systems - target conditioning, chamber qualification, substrate preparation, and recipe troubleshooting.
Basic thin-film characterization experience: you know how to read an XRD pattern, interpret an ellipsometry fit, and recognize a SEM image that signals a process problem.
Strong documentation habits and attention to detail. You log what you did, not just what you intended to do, and you understand why that distinction matters in a data-driven science environment.
Ability to ramp up quickly on new equipment and experimental workflows, and comfort operating independently in shared research facilities where you are responsible for your own training and access.
Experience working in university nanofabrication facilities or shared cleanroom environments — including completing facility-specific safety training, navigating tool reservation systems, and operating within shared-use norms.
Exposure to functional materials in thin-film form: superconductors, magnetics, ferroelectrics, thermoelectrics, or multi-layer device stacks relevant to memory or semiconductor applications.
Familiarity with LIMS or other lab information systems used to track samples, experiments, and characterization results.
Experience with wafer-level metrology: film thickness mapping, stress/warpage measurement, or 4-point probe resistivity mapping at wafer scale.
Interest in working at the intersection of experimental science and AI-driven discovery.
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada (Soon: San Francisco, too)
Compensation: $180,000–$225,000
This is a 12-month fixed-term position, with the potential to convert to full time.
Visa sponsorship: Yes, we sponsor visas and will do everything we can do assist in this process.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nJoin our world-class team of scientists and engineers building a lab where AI and automation speed up physical R&D.\n\nPeriodic Labs is developing AI that can both simulate science and verify its predictions to train on the full scientific method. A key challenge is the gap between bulk materials discovery and thin-film form: materials our AI predicts and our powder lab synthesizes must ultimately be validated as scalable thin films to be relevant to semiconductor, memory, and advanced materials applications. We are building a dedicated thin-film lab while generating early data at partner facilities.\n\nWe're looking for a hands-on Research Associate in Thin Films to run advanced deposition and nanofabrication processes, generate high-quality experimental data, and collaborate closely with our AI and materials teams. This is a 12-month fixed-term position with the potential to convert to full time.\n\nIn the near term you will operate at external partner facilities before Periodic’s own tools come online. As the in-house lab is commissioned, you will transition to running experiments on deposition and metrology suite. \n\n\n\n\nWHAT YOU’LL DO\n\n - As a process module owner, you will execute thin-film deposition and related nanofabrication processes.\n\n - Prepare substrates, manage process flows, and maintain detailed experimental records that meet the metadata and data quality standards for AI training. Every experiment you run is a potential data point for our models - documentation quality matters as much as deposition quality.\n\n - Perform structural and functional thin-film characterization: XRD/XRR for structure and thickness, ellipsometry and profilometry for film properties, SEM/EDX for morphology and composition, and 4-point probe and basic transport measurements for electrical properties.\n\n - Monitor in-situ metrology during deposition to ensure high quality film growth.\n\n - Collaborate with the AI and materials science teams to help define which deposition parameters to vary, interpreting film characterization results in context of what the AI predicts, and flagging discrepancies that may indicate new physics or synthesis insights.\n\n - Troubleshoot process issues and iterate quickly on recipes under guidance from senior team members. Escalate anomalies rather than work around them, and document both failures and fixes in a format that preserves institutional knowledge.\n\n\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - Currently pursuing or recently completed a PhD (or advanced graduate degree) in materials science, physics, chemistry, or a related field.\n\n - Hands-on experience operating thin-film deposition equipment - sputtering, evaporation, PLD, ALD, CVD, MBE, or related techniques - developed in a university or research lab environment.\n\n - Familiarity with the practical realities of these systems - target conditioning, chamber qualification, substrate preparation, and recipe troubleshooting.\n\n - Basic thin-film characterization experience: you know how to read an XRD pattern, interpret an ellipsometry fit, and recognize a SEM image that signals a process problem.\n\n - Strong documentation habits and attention to detail. You log what you did, not just what you intended to do, and you understand why that distinction matters in a data-driven science environment.\n\n - Ability to ramp up quickly on new equipment and experimental workflows, and comfort operating independently in shared research facilities where you are responsible for your own training and access.\n\n\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience working in university nanofabrication facilities or shared cleanroom environments — including completing facility-specific safety training, navigating tool reservation systems, and operating within shared-use norms.\n\n - Exposure to functional materials in thin-film form: superconductors, magnetics, ferroelectrics, thermoelectrics, or multi-layer device stacks relevant to memory or semiconductor applications.\n\n - Familiarity with LIMS or other lab information systems used to track samples, experiments, and characterization results.\n\n - Experience with wafer-level metrology: film thickness mapping, stress/warpage measurement, or 4-point probe resistivity mapping at wafer scale.\n\n - Interest in working at the intersection of experimental science and AI-driven discovery.\n\n\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA or Montreal, Canada (Soon: San Francisco, too)\n\nCompensation: $180,000–$225,000\n\nThis is a 12-month fixed-term position, with the potential to convert to full time.\n\nVisa sponsorship: Yes, we sponsor visas and will do everything we can do assist in this process."},{"id":"d039ec58-a97d-47e1-b1e5-db003d772f77","title":"Research Scientist, Data","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[{"location":"Montreal, Canada","address":{"postalAddress":{"addressRegion":"Quebec","addressCountry":"Canada","addressLocality":"Montreal"}}}],"publishedAt":"2026-07-25T00:34:40.089+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/d039ec58-a97d-47e1-b1e5-db003d772f77","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/d039ec58-a97d-47e1-b1e5-db003d772f77/application","descriptionHtml":"The most important scientific discoveries of our time won’t happen in a traditional lab. We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
You will work on the most important aspect of Scientific AI creation: evaluations and data. This means constructing cutting-edge evaluations based on advanced scientific use cases, sourcing and procuring external datasets, integrating internally generated experimental data into the training stack, constructing training environments for RL. You’ll ensure that the team always has the right assets, in the right shape, to evaluate and improve AI models.
You will work with computational and experimental scientists to translate complex scientific workflows into rigorous evaluations and agentic benchmarks, and partner with pretraining, midtraining, and reinforcement learning researchers to identify the data models needed, then build the datasets, environments, and pipelines to deliver it. Your goal will be to create a tight feedback loop between scientific use cases, model evaluation, and training data.
Own the evaluation and data strategy across the training stack, identifying capability gaps and shaping the roadmap with leads of physical science and AI research
Work with domain experts to translate advanced scientific workflows into rigorous evals, benchmarks, and RL environments
Source, evaluate, and procure external datasets across chemistry, physics, materials science, mathematics, simulations, and laboratory instrumentation
Build robust pipelines to ingest, clean, and transform for training large-scale datasets from heterogeneous sources
Build tooling and analysis workflows that help researchers inspect data, understand model failures, and determine which evaluations or datasets to develop next
Designed evaluations, benchmarks, or RL environments for language models, agents, or scientific AI systems
Built large-scale data pipelines for LLM pretraining, midtraining, post-training, or evaluation
Strong judgment about dataset and evaluation quality, including scientific relevance, coverage, provenance, licensing, and contamination risks
Strong software and data engineering skills, including familiarity with data processing at scale, dataset versioning, lineage tracking
A research-oriented mindset: you form hypotheses about data, run controlled experiments, measure model outcomes, and iterate with rigor
Research experience in areas such as materials science, solid state chemistry, chemistry, computational physics, semiconductors
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $250,000-350,000 + equity
Visa sponsorship: Yes, we sponsor visas.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nThe most important scientific discoveries of our time won’t happen in a traditional lab. We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nYou will work on the most important aspect of Scientific AI creation: evaluations and data. This means constructing cutting-edge evaluations based on advanced scientific use cases, sourcing and procuring external datasets, integrating internally generated experimental data into the training stack, constructing training environments for RL. You’ll ensure that the team always has the right assets, in the right shape, to evaluate and improve AI models.\n\nYou will work with computational and experimental scientists to translate complex scientific workflows into rigorous evaluations and agentic benchmarks, and partner with pretraining, midtraining, and reinforcement learning researchers to identify the data models needed, then build the datasets, environments, and pipelines to deliver it. Your goal will be to create a tight feedback loop between scientific use cases, model evaluation, and training data.\n\n\n\n \n\n\nWHAT YOU’LL DO\n\n - Own the evaluation and data strategy across the training stack, identifying capability gaps and shaping the roadmap with leads of physical science and AI research\n\n - Work with domain experts to translate advanced scientific workflows into rigorous evals, benchmarks, and RL environments\n\n - Source, evaluate, and procure external datasets across chemistry, physics, materials science, mathematics, simulations, and laboratory instrumentation\n\n - Build robust pipelines to ingest, clean, and transform for training large-scale datasets from heterogeneous sources\n\n - Build tooling and analysis workflows that help researchers inspect data, understand model failures, and determine which evaluations or datasets to develop next\n \n \n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - Designed evaluations, benchmarks, or RL environments for language models, agents, or scientific AI systems\n\n - Built large-scale data pipelines for LLM pretraining, midtraining, post-training, or evaluation\n\n - Strong judgment about dataset and evaluation quality, including scientific relevance, coverage, provenance, licensing, and contamination risks\n\n - Strong software and data engineering skills, including familiarity with data processing at scale, dataset versioning, lineage tracking\n\n - A research-oriented mindset: you form hypotheses about data, run controlled experiments, measure model outcomes, and iterate with rigor\n\n - Research experience in areas such as materials science, solid state chemistry, chemistry, computational physics, semiconductors\n\n\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\nCompensation: $250,000-350,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas."},{"id":"d9180228-c113-4d5f-a4d6-793994e50b7c","title":"ML Systems Engineer","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-04-29T14:55:07.829+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/d9180228-c113-4d5f-a4d6-793994e50b7c","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/d9180228-c113-4d5f-a4d6-793994e50b7c/application","descriptionHtml":"We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
You’ll work alongside some of the world’s leading ML systems engineers, including leaders behind Megatron-LM, SGLang, Liger Kernel, TorchRec, CleanRL, TorchRL, and JAX-MD.
We’re looking for exceptional ML Systems Engineers to build the agentic infrastructure powering our large-scale training, inference, and reinforcement learning. You’ll own critical pieces of the ML systems stack to maximize performance, scalability, reliability, and productivity for both engineers and AI agents.
Build and optimize large-scale training and reinforcement learning infrastructure while ensuring its correctness
Develop high-performance inference and serving systems
Design distributed runtimes and scheduling systems for complex ML workloads
Build secure and large-scale sandboxing and execution environments
Optimize memory, GPU kernels and communication for maximum throughput and end-to-end efficiency
Improve scalability, reliability, and efficiency across the ML systems stack
Strong systems programming and performance engineering skills
Experience building high-performance ML infrastructure at scale
Ability to own complex technical problems end-to-end
Strong coding ability and engineering judgment, including the ability to work effectively with AI agents to design, implement, test, and debug complex systems
High ownership, fast execution, and a passion for pushing the frontier of AI systems and accelerating scientific discovery
Training: Strong experience building, debugging and optimizing large-scale training systems with Megatron-LM. Familiarity with TorchTitan, FSDP, veRL, Slime, or other distributed training systems is a plus.
Distributed Runtime: Strong experience with Ray. Familiarity with Monarch or other distributed execution frameworks is a plus.
Inference: Strong experience with SGLang. Familiarity with vLLM, TensorRT-LLM, or production LLM serving systems is a plus.
Sandboxing: Strong experience with secure execution environments, containers, virtualization, or code sandboxing.
GPU Kernels: Strong experience with CUDA, Triton, CUTLASS, CuTe, or custom GPU kernel development.
GPU Communication: Strong experience with NCCL, NVLink, InfiniBand, RDMA, GPUDirect RDMA, or large-scale communication optimization.
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $250,000-$350,000 base + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nYou’ll work alongside some of the world’s leading ML systems engineers, including leaders behind Megatron-LM, SGLang, Liger Kernel, TorchRec, CleanRL, TorchRL, and JAX-MD.\n\nWe’re looking for exceptional ML Systems Engineers to build the agentic infrastructure powering our large-scale training, inference, and reinforcement learning. You’ll own critical pieces of the ML systems stack to maximize performance, scalability, reliability, and productivity for both engineers and AI agents.\n\n\n\n\nWHAT YOU'LL DO\n\n - Build and optimize large-scale training and reinforcement learning infrastructure while ensuring its correctness\n\n - Develop high-performance inference and serving systems\n\n - Design distributed runtimes and scheduling systems for complex ML workloads\n\n - Build secure and large-scale sandboxing and execution environments\n\n - Optimize memory, GPU kernels and communication for maximum throughput and end-to-end efficiency\n\n - Improve scalability, reliability, and efficiency across the ML systems stack\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\n - Strong systems programming and performance engineering skills\n\n - Experience building high-performance ML infrastructure at scale\n\n - Ability to own complex technical problems end-to-end\n\n - Strong coding ability and engineering judgment, including the ability to work effectively with AI agents to design, implement, test, and debug complex systems\n\n - High ownership, fast execution, and a passion for pushing the frontier of AI systems and accelerating scientific discovery\n\n\n\nYOU SHOULD HAVE DEEP EXPERTISE IN AT LEAST ONE OF THE FOLLOWING:\n\n - Training: Strong experience building, debugging and optimizing large-scale training systems with Megatron-LM. Familiarity with TorchTitan, FSDP, veRL, Slime, or other distributed training systems is a plus.\n\n - Distributed Runtime: Strong experience with Ray. Familiarity with Monarch or other distributed execution frameworks is a plus.\n\n - Inference: Strong experience with SGLang. Familiarity with vLLM, TensorRT-LLM, or production LLM serving systems is a plus.\n\n - Sandboxing: Strong experience with secure execution environments, containers, virtualization, or code sandboxing.\n\n - GPU Kernels: Strong experience with CUDA, Triton, CUTLASS, CuTe, or custom GPU kernel development.\n\n - GPU Communication: Strong experience with NCCL, NVLink, InfiniBand, RDMA, GPUDirect RDMA, or large-scale communication optimization.\n \n \n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA (Soon: San Francisco, too)\n\nCompensation: $250,000-$350,000 base + equity\n\nVisa sponsorship: Yes, we sponsor visas.\n\n\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"21b61a4d-92ff-4f98-9a7c-251f02966988","title":"Process Engineer, Powder","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-05-08T22:58:42.650+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/21b61a4d-92ff-4f98-9a7c-251f02966988","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/21b61a4d-92ff-4f98-9a7c-251f02966988/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
As Periodic Labs scales the experimental engine behind our AI-driven materials discovery platform, we’re hiring a Process Engineer to own the end-to-end workflow of our powder synthesis lab. You’ll work directly across dispensing, mixing, pressing, reaction, recovery, and characterization — building the systems, controls, and instincts that keep a high-mix, fast-moving research process producing trustworthy data at increasing throughput.
This is a hands-on, jack-of-all-trades role. You’ll move fluently between equipment troubleshooting, statistical process control, operator workflows, and the underlying science. The variation here is intentional — we run an enormous diversity of chemistries — and your job is to build the systems that absorb that intended variation while ruthlessly separating out the unintended kind. What you learn stabilizing the manual lab will directly shape how we design our automated, full-scale lab.
Own the powder synthesis workflow end-to-end — dispensing, mixing, pressing, reaction, recovery, and characterization — ensuring the process runs smoothly as throughput and complexity grow
Map failure modes across the full process flow and design comprehensive systems and controls so failures either don’t happen or are caught and recovered quickly
Apply statistical process control (SPC) and systems thinking to track key process inputs and outputs, identify drift, and bring processes into a stable, predictable state
Troubleshoot and diagnose equipment issues across the lab — dispensing heads, reaction chambers, characterization tools — and drive root-cause investigations to durable fixes
Investigate data integrity issues across the toolchain, including cases where equipment dispenses correctly but uploads data incorrectly, and partner with software and infra to adjust scripts and instrumentation
Design operator-facing workflows that prevent sample mix-ups and reduce variation introduced by human handoffs
Run design of experiments (DOE) to identify which recipe and process factors most impact outcomes, and use structured methodologies to converge efficiently
Partner with research scientists, lab engineers, and software teams to translate the lessons from the manual lab into requirements for the automated, full-scale lab
Establish quality and reliability practices that scale with us — process documentation, control plans, and feedback loops between operators, scientists, and the data systems
A degree in chemistry, materials science, chemical engineering, or a related field, with hands-on experience in solid-state chemistry, ceramics, or powder processing
Experience as a process engineer (or closely adjacent role) in a high-mix R&D, pilot, or manufacturing environment — ideally one that involved both intentional recipe variation and tight process discipline
Strong systems thinking — you can break an unfamiliar process into clear inputs, outputs, and unit operations, and quickly build mental models of how the black boxes inside actually behave
Working knowledge of statistical process control (SPC), six sigma or lean concepts, and design of experiments (DOE), with comfort using tools like JMP or Minitab
Hands-on familiarity with characterization techniques relevant to powders and ceramics — e.g., X-ray diffraction (XRD), scanning electron microscopy (SEM) — and with high-temperature processing of ceramic materials
Comfort with equipment troubleshooting and a healthy bias toward getting your hands on the tool, the data, and the operator workflow when something goes wrong
Some computer savvy — enough to read and lightly modify scripts, validate data flows, and partner effectively with software engineers when instrumentation or data pipelines need adjustment
Strong ownership, bias for action, and the judgment to know when to stabilize what exists versus when to redesign it
Clear communication and the ability to work cross-functionally with researchers, lab operators, equipment vendors, and software teams
Experience at companies working on battery materials, anode/cathode chemistries, or other powder- and ceramic-heavy processes (e.g., Tesla, Sila, Mitra Chem, 24M, or similar)
Background spanning multiple unit operations — you’ve had to come up to speed quickly on processes you didn’t design
Experience scaling an R&D or pilot process toward higher throughput or automation
Exposure to quality engineering, reliability engineering, or process development roles, and an interest in growing into deeper specialization over time
Familiarity with how scientific instrumentation integrates with data systems, and an instinct for separating equipment problems from data-pipeline problems
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $225,000-300,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nAs Periodic Labs scales the experimental engine behind our AI-driven materials discovery platform, we’re hiring a Process Engineer to own the end-to-end workflow of our powder synthesis lab. You’ll work directly across dispensing, mixing, pressing, reaction, recovery, and characterization — building the systems, controls, and instincts that keep a high-mix, fast-moving research process producing trustworthy data at increasing throughput.\n\nThis is a hands-on, jack-of-all-trades role. You’ll move fluently between equipment troubleshooting, statistical process control, operator workflows, and the underlying science. The variation here is intentional — we run an enormous diversity of chemistries — and your job is to build the systems that absorb that intended variation while ruthlessly separating out the unintended kind. What you learn stabilizing the manual lab will directly shape how we design our automated, full-scale lab.\n\n\n\n\nWHAT YOU’LL DO\n\n - Own the powder synthesis workflow end-to-end — dispensing, mixing, pressing, reaction, recovery, and characterization — ensuring the process runs smoothly as throughput and complexity grow\n\n - Map failure modes across the full process flow and design comprehensive systems and controls so failures either don’t happen or are caught and recovered quickly\n\n - Apply statistical process control (SPC) and systems thinking to track key process inputs and outputs, identify drift, and bring processes into a stable, predictable state\n\n - Troubleshoot and diagnose equipment issues across the lab — dispensing heads, reaction chambers, characterization tools — and drive root-cause investigations to durable fixes\n\n - Investigate data integrity issues across the toolchain, including cases where equipment dispenses correctly but uploads data incorrectly, and partner with software and infra to adjust scripts and instrumentation\n\n - Design operator-facing workflows that prevent sample mix-ups and reduce variation introduced by human handoffs\n\n - Run design of experiments (DOE) to identify which recipe and process factors most impact outcomes, and use structured methodologies to converge efficiently\n\n - Partner with research scientists, lab engineers, and software teams to translate the lessons from the manual lab into requirements for the automated, full-scale lab\n\n - Establish quality and reliability practices that scale with us — process documentation, control plans, and feedback loops between operators, scientists, and the data systems\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - A degree in chemistry, materials science, chemical engineering, or a related field, with hands-on experience in solid-state chemistry, ceramics, or powder processing\n\n - Experience as a process engineer (or closely adjacent role) in a high-mix R&D, pilot, or manufacturing environment — ideally one that involved both intentional recipe variation and tight process discipline\n\n - Strong systems thinking — you can break an unfamiliar process into clear inputs, outputs, and unit operations, and quickly build mental models of how the black boxes inside actually behave\n\n - Working knowledge of statistical process control (SPC), six sigma or lean concepts, and design of experiments (DOE), with comfort using tools like JMP or Minitab\n\n - Hands-on familiarity with characterization techniques relevant to powders and ceramics — e.g., X-ray diffraction (XRD), scanning electron microscopy (SEM) — and with high-temperature processing of ceramic materials\n\n - Comfort with equipment troubleshooting and a healthy bias toward getting your hands on the tool, the data, and the operator workflow when something goes wrong\n\n - Some computer savvy — enough to read and lightly modify scripts, validate data flows, and partner effectively with software engineers when instrumentation or data pipelines need adjustment\n\n - Strong ownership, bias for action, and the judgment to know when to stabilize what exists versus when to redesign it\n\n - Clear communication and the ability to work cross-functionally with researchers, lab operators, equipment vendors, and software teams\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience at companies working on battery materials, anode/cathode chemistries, or other powder- and ceramic-heavy processes (e.g., Tesla, Sila, Mitra Chem, 24M, or similar)\n\n - Background spanning multiple unit operations — you’ve had to come up to speed quickly on processes you didn’t design\n\n - Experience scaling an R&D or pilot process toward higher throughput or automation\n\n - Exposure to quality engineering, reliability engineering, or process development roles, and an interest in growing into deeper specialization over time\n\n - Familiarity with how scientific instrumentation integrates with data systems, and an instinct for separating equipment problems from data-pipeline problems\n\n\nMECHANICS\n\n - Minimum education: Bachelor’s degree or similar experience\n\n - Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)\n\n - Compensation: $225,000-300,000 + equity\n\n - Visa sponsorship: Yes, we sponsor visas.\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"e58cc4ac-39a8-4f46-a660-4cab443922cc","title":"Procurement & Finance Operations Manager","department":"Business and Operations","team":"Business and Operations","employmentType":"Contract","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-05-21T19:18:36.383+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/e58cc4ac-39a8-4f46-a660-4cab443922cc","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/e58cc4ac-39a8-4f46-a660-4cab443922cc/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
We are seeking a highly analytical, systems-oriented Procurement & Finance Operations Manager to own procurement, inventory strategy, operational finance, and purchasing systems across our laboratory and R&D environments.
This role sits at the intersection of scientific operations and finance. You will help build the operational infrastructure required to scale experimentation volume dramatically while maintaining financial discipline, inventory reliability, and operational efficiency.
You will own the full lifecycle of lab procurement and financial operations — from vendor management and inventory forecasting to purchase order workflows, budgeting, spend analytics, and experiment cost modeling. A key responsibility of this role will be developing systems and processes that enable the company to understand and optimize the true cost of experimentation across materials, compute, capital equipment, and operational overhead.
This is not a traditional procurement role. We are looking for someone who can think deeply about operational systems, financial rigor, automation opportunities, and scalable workflows in a rapidly evolving technical environment.
Own purchasing operations across lab consumables, specialty materials, gases, chemicals, equipment, and operational supplies
Develop inventory forecasting systems and consumption tracking processes to prevent stockouts and support rapidly scaling experimental throughput
Build systems to analyze and track the true cost of scientific experiments across materials, compute, equipment utilization, and operational overhead
Own purchase order generation, invoice reconciliation, and three-way matching workflows across procurement and accounting processes
Track operational and capital expenditures against budgets and support forecasting, reporting, and cost optimization initiatives
Design and implement scalable procurement, inventory, and operational finance systems as the organization grows
Improve workflows through automation, tooling, inventory tracking systems, dashboards, and process optimization initiatives
Partner closely with scientists, engineers, lab operations, finance, and leadership teams to support evolving experimental needs
Manage supplier and vendor relationships, including pricing negotiations, lead times, and purchasing agreements
Identify operational bottlenecks and help build the infrastructure and processes required to scale high-throughput R&D environments
Experience in advanced materials, hardware, robotics, biotech, semiconductor, or scientific lab environments
Experience building procurement or inventory systems from scratch
Experience implementing inventory tracking systems (QR/barcode workflows, inventory software, etc.)
Experience with operational finance, manufacturing finance, or COGS analysis
Experience supporting high-throughput R&D or experimental environments
Familiarity with automation workflows, reporting systems, or operational tooling
Basic financial modeling and analytics skills
5+ years of experience in procurement, operational finance, lab operations, supply chain, or related operational roles
Experience supporting technical, scientific, manufacturing, hardware, or R&D environments
Strong understanding of budgeting, forecasting, spend tracking, and operational analytics
Experience owning procurement workflows, purchasing operations, and vendor management
Experience with PO, accounting, and spend management systems (e.g., Ramp, QuickBooks, NetSuite, SAP, Coupa, Quartzy, etc.)
Strong systems-thinking mindset with demonstrated process improvement experience
Comfortable operating in ambiguous, fast-changing startup environments
Highly organized with exceptional attention to detail
Strong cross-functional communication skills and ability to work closely with technical teams
Minimum education: Bachelor’s degree or similar experience
Location: Our lab is located in Menlo Park, CA
Term: 12-month fixed-term position with potential to convert to full time
Compensation: The annual compensation range for this role is $80-$150 an hour
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nWe are seeking a highly analytical, systems-oriented Procurement & Finance Operations Manager to own procurement, inventory strategy, operational finance, and purchasing systems across our laboratory and R&D environments.\n\nThis role sits at the intersection of scientific operations and finance. You will help build the operational infrastructure required to scale experimentation volume dramatically while maintaining financial discipline, inventory reliability, and operational efficiency.\n\nYou will own the full lifecycle of lab procurement and financial operations — from vendor management and inventory forecasting to purchase order workflows, budgeting, spend analytics, and experiment cost modeling. A key responsibility of this role will be developing systems and processes that enable the company to understand and optimize the true cost of experimentation across materials, compute, capital equipment, and operational overhead.\n\nThis is not a traditional procurement role. We are looking for someone who can think deeply about operational systems, financial rigor, automation opportunities, and scalable workflows in a rapidly evolving technical environment.\n\n\n\n\nWHAT YOU’LL DO\n\n - Own purchasing operations across lab consumables, specialty materials, gases, chemicals, equipment, and operational supplies\n\n - Develop inventory forecasting systems and consumption tracking processes to prevent stockouts and support rapidly scaling experimental throughput\n\n - Build systems to analyze and track the true cost of scientific experiments across materials, compute, equipment utilization, and operational overhead\n\n - Own purchase order generation, invoice reconciliation, and three-way matching workflows across procurement and accounting processes\n\n - Track operational and capital expenditures against budgets and support forecasting, reporting, and cost optimization initiatives\n\n - Design and implement scalable procurement, inventory, and operational finance systems as the organization grows\n\n - Improve workflows through automation, tooling, inventory tracking systems, dashboards, and process optimization initiatives\n\n - Partner closely with scientists, engineers, lab operations, finance, and leadership teams to support evolving experimental needs\n\n - Manage supplier and vendor relationships, including pricing negotiations, lead times, and purchasing agreements\n\n - Identify operational bottlenecks and help build the infrastructure and processes required to scale high-throughput R&D environments\n \n \n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience in advanced materials, hardware, robotics, biotech, semiconductor, or scientific lab environments\n\n - Experience building procurement or inventory systems from scratch\n\n - Experience implementing inventory tracking systems (QR/barcode workflows, inventory software, etc.)\n\n - Experience with operational finance, manufacturing finance, or COGS analysis\n\n - Experience supporting high-throughput R&D or experimental environments\n\n - Familiarity with automation workflows, reporting systems, or operational tooling\n\n - Basic financial modeling and analytics skills\n \n \n\n\nQUALIFICATIONS\n\n - 5+ years of experience in procurement, operational finance, lab operations, supply chain, or related operational roles\n\n - Experience supporting technical, scientific, manufacturing, hardware, or R&D environments\n\n - Strong understanding of budgeting, forecasting, spend tracking, and operational analytics\n\n - Experience owning procurement workflows, purchasing operations, and vendor management\n\n - Experience with PO, accounting, and spend management systems (e.g., Ramp, QuickBooks, NetSuite, SAP, Coupa, Quartzy, etc.)\n\n - Strong systems-thinking mindset with demonstrated process improvement experience\n\n - Comfortable operating in ambiguous, fast-changing startup environments\n\n - Highly organized with exceptional attention to detail\n\n - Strong cross-functional communication skills and ability to work closely with technical teams\n \n \n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Our lab is located in Menlo Park, CA\n\nTerm: 12-month fixed-term position with potential to convert to full time\n\nCompensation: The annual compensation range for this role is $80-$150 an hour\n\nVisa sponsorship: Yes, we sponsor visas.\n\n\n\nWe’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.\n\n"},{"id":"2cfb099d-42f1-4dff-93f4-1862b13f914a","title":"Research Intern, Thin Films","department":"Science","team":"Science","employmentType":"Intern","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-05-26T20:20:52.070+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/2cfb099d-42f1-4dff-93f4-1862b13f914a","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/2cfb099d-42f1-4dff-93f4-1862b13f914a/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
Periodic Labs is developing AI that can both simulate science and verify its predictions to train on the full scientific method. A central challenge in that mission is connecting materials discovery with real, scalable device-relevant form factors. Materials our AI predicts and our lab synthesizes must ultimately be validated through thin films, patterned structures, and device-relevant process flows for applications across semiconductors, memory, photonics, and advanced materials.
We are looking for a hands-on Research Intern with experience in cleanroom-based microfabrication or nanofabrication. This person should have practical exposure to lithography, deposition, and etch processes for silicon-based microelectronic, photonic, MEMS, or optical devices.
In this role, you will support process development and experimental execution while contributing to the buildout of Periodic’s internal thin-film and nanofabrication capabilities. Your work will help generate high-quality experimental data that feeds directly into our AI training pipeline.
Execute hands-on nanofabrication processes for silicon-based microelectronic, photonic, MEMS, or optical devices, including lithography, thin-film deposition, etch, substrate preparation, and related cleanroom workflows.
Support lithography processes such as spin coating, baking, mask alignment, exposure, development, lift-off, and optical inspection.
Operate or support thin-film deposition processes such as sputtering, evaporation, PVD, PLD, ALD, PECVD, or related techniques.
Run or assist with etch processes such as wet etching, plasma etching, RIE, ICP-RIE, or other dry etch workflows.
Prepare substrates, manage process flows, track samples, and maintain detailed experimental records that meet the metadata and data quality standards required for AI training.
Perform basic structural, optical, electrical, or morphological characterization, potentially including profilometry, ellipsometry, SEM, optical microscopy, XRD/XRR, 4-point probe, or related metrology.
Work with senior scientists and engineers to troubleshoot process issues, identify failure modes, and iterate on recipes or workflows.
Collaborate with materials science, AI, and automation teams to connect fabrication results with model predictions and experimental planning.
Follow rigorous laboratory safety and facility protocols, including those required by external shared cleanroom facilities.
Currently pursuing or recently completed a Bachelor’s, Master’s, or PhD in electrical engineering, materials science, applied physics, mechanical engineering, chemical engineering, chemistry, or a related field.
Hands-on experience in a university cleanroom, nanofabrication facility, semiconductor lab, photonics lab, MEMS lab, or related research environment.
Practical exposure to lithography, deposition, and etch processes. You do not need to be equally deep in every module, but you should understand how these steps connect in a device fabrication flow.
Experience working with silicon-based microelectronic, photonic, MEMS, optical, or semiconductor devices.
Comfort spending real time at tools, following cleanroom protocols, logging process details, and learning new equipment quickly.
Strong documentation habits and attention to detail. You record what actually happened in the experiment, not just what was intended.
Ability to work independently in shared research facilities while escalating issues appropriately and learning from senior team members.
Experience with full or partial device fabrication flows involving lithography, deposition, etch, and characterization.
Hands-on experience with specific tools or techniques such as mask aligners, spin coaters, sputtering, evaporation, ALD, PECVD, RIE, ICP-RIE, profilometry, ellipsometry, SEM, or 4-point probe.
Experience fabricating silicon photonics, MEMS, optoelectronic devices, sensors, thin-film devices, or other micro/nanoscale structures.
Experience working in shared cleanroom environments, including completing facility-specific safety training, navigating tool reservation systems, and operating within shared-use norms.
Exposure to functional materials in thin-film or device form, including oxides, nitrides, metals, semiconductors, superconductors, magnetics, ferroelectrics, or multilayer stacks.
Interest in working at the intersection of experimental science, nanofabrication, and AI-driven discovery.
Location: Menlo Park, CA. This role is expected to be on-site, with work taking place at Periodic’s lab and external cleanroom facilities in the Bay Area.
Term: Internship / fixed-term position.
Compensation: Competitive and based on experience.
Visa sponsorship: We sponsor visas and will do everything we can to assist in this process with our legal support.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\nABOUT THE ROLE\n\nPeriodic Labs is developing AI that can both simulate science and verify its predictions to train on the full scientific method. A central challenge in that mission is connecting materials discovery with real, scalable device-relevant form factors. Materials our AI predicts and our lab synthesizes must ultimately be validated through thin films, patterned structures, and device-relevant process flows for applications across semiconductors, memory, photonics, and advanced materials.\n\nWe are looking for a hands-on Research Intern with experience in cleanroom-based microfabrication or nanofabrication. This person should have practical exposure to lithography, deposition, and etch processes for silicon-based microelectronic, photonic, MEMS, or optical devices.\n\nIn this role, you will support process development and experimental execution while contributing to the buildout of Periodic’s internal thin-film and nanofabrication capabilities. Your work will help generate high-quality experimental data that feeds directly into our AI training pipeline.\n\n\n\nWHAT YOU’LL DO\n\n - Execute hands-on nanofabrication processes for silicon-based microelectronic, photonic, MEMS, or optical devices, including lithography, thin-film deposition, etch, substrate preparation, and related cleanroom workflows.\n\n - Support lithography processes such as spin coating, baking, mask alignment, exposure, development, lift-off, and optical inspection.\n\n - Operate or support thin-film deposition processes such as sputtering, evaporation, PVD, PLD, ALD, PECVD, or related techniques.\n\n - Run or assist with etch processes such as wet etching, plasma etching, RIE, ICP-RIE, or other dry etch workflows.\n\n - Prepare substrates, manage process flows, track samples, and maintain detailed experimental records that meet the metadata and data quality standards required for AI training.\n\n - Perform basic structural, optical, electrical, or morphological characterization, potentially including profilometry, ellipsometry, SEM, optical microscopy, XRD/XRR, 4-point probe, or related metrology.\n\n - Work with senior scientists and engineers to troubleshoot process issues, identify failure modes, and iterate on recipes or workflows.\n\n - Collaborate with materials science, AI, and automation teams to connect fabrication results with model predictions and experimental planning.\n\n - Follow rigorous laboratory safety and facility protocols, including those required by external shared cleanroom facilities.\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - Currently pursuing or recently completed a Bachelor’s, Master’s, or PhD in electrical engineering, materials science, applied physics, mechanical engineering, chemical engineering, chemistry, or a related field.\n\n - Hands-on experience in a university cleanroom, nanofabrication facility, semiconductor lab, photonics lab, MEMS lab, or related research environment.\n\n - Practical exposure to lithography, deposition, and etch processes. You do not need to be equally deep in every module, but you should understand how these steps connect in a device fabrication flow.\n\n - Experience working with silicon-based microelectronic, photonic, MEMS, optical, or semiconductor devices.\n\n - Comfort spending real time at tools, following cleanroom protocols, logging process details, and learning new equipment quickly.\n\n - Strong documentation habits and attention to detail. You record what actually happened in the experiment, not just what was intended.\n\n - Ability to work independently in shared research facilities while escalating issues appropriately and learning from senior team members.\n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - Experience with full or partial device fabrication flows involving lithography, deposition, etch, and characterization.\n\n - Hands-on experience with specific tools or techniques such as mask aligners, spin coaters, sputtering, evaporation, ALD, PECVD, RIE, ICP-RIE, profilometry, ellipsometry, SEM, or 4-point probe.\n\n - Experience fabricating silicon photonics, MEMS, optoelectronic devices, sensors, thin-film devices, or other micro/nanoscale structures.\n\n - Experience working in shared cleanroom environments, including completing facility-specific safety training, navigating tool reservation systems, and operating within shared-use norms.\n\n - Exposure to functional materials in thin-film or device form, including oxides, nitrides, metals, semiconductors, superconductors, magnetics, ferroelectrics, or multilayer stacks.\n\n - Interest in working at the intersection of experimental science, nanofabrication, and AI-driven discovery.\n\n\nMECHANICS\n\nLocation: Menlo Park, CA. This role is expected to be on-site, with work taking place at Periodic’s lab and external cleanroom facilities in the Bay Area.\n\nTerm: Internship / fixed-term position.\n\nCompensation: Competitive and based on experience.\n\nVisa sponsorship: We sponsor visas and will do everything we can to assist in this process with our legal support.\n\n"},{"id":"1bab7e17-20fd-4b82-a152-98b96375a626","title":"Forward Deployed Engineer, Physics & Simulation","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-06-03T16:22:34.376+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/1bab7e17-20fd-4b82-a152-98b96375a626","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/1bab7e17-20fd-4b82-a152-98b96375a626/application","descriptionHtml":"We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
We’re using AI-driven simulation to solve hard physical process optimization problems in advanced manufacturing. As a forward deployed engineer focused on physics and simulation, you will be the technical backbone of our most demanding customer engagements – spending significant time on-site, embedding directly with customer teams, and owning simulation workflows end-to-end.
You’ll work with our modeling and ML teams to build and calibrate physics-based simulations, turn customer process knowledge into computational models, and drive recipe optimization with direct feedback loops to production. This is a hands-on, high-ownership role at the frontier of AI for physical science.
This role requires travel to and extended time on-site in Taiwan.
Own the simulation workflow end-to-end for customer engagements, from model setup and calibration through optimization and results interpretation
Run, debug and modify physics-based simulations of complex physical processes in diverse domains, such as microfluidics, charge transport and structural deformation
Work on-site with customer engineering teams on-site to understand process constraints, interpret simulation results into real process improvements
Write tools, skills and agents to reliably drive end-to-end LLM-based simulation workflows, including experimental validation, parameter fitting and recipe optimization
Build and extend simulation tooling in Python – job submission, parameter sweeps, output parsing, integration
Feed domain insights back to the research and product teams, shaping the next version our platform
A strong foundation in numerical simulation of continuum systems – fluid dynamics, heat transfer, structural mechanics, electromagnetics, or similar – gained through graduate research, industry, or both
Hands-on experience solving partial differential equations numerically, including mesh generation, solver tuning, and debugging numerical instabilities
Solid Python skills for scripting and scientific computing (NumPy, SciPy, or similar)
A process engineer’s instinct: you treat simulations as tools for answering real process questions, not just jobs to run
Strong communication skills and genuine comfort working directly with customer engineers
Willingness to spend extended periods on-site in Taiwan
A self-starter mindset: you can take a technical problem from definition to deployed result without much hand-holding
CFD background, including tools like OpenFOAM, ANSYS Fluent, Star-CCM+, or custom solvers
Grad-level research experience building simulation software in domains like mechanical or chemical engineering, weather modeling, astrophysics, or materials processing
Familiar with semiconductor manufacturing processes
Familiarity with physics-informed ML, surrogate modeling, or neural operators applied to simulation acceleration
Experience integrating simulation tools into larger software platforms or automated optimization pipelines
Mandarin proficiency for on-site collaboration in Taiwan
Lab or experimental background, with an appreciation for how simulation connects to physical data
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too) + frequent travel to Taiwan
Compensation: $200,000-$275,000 + equity
Visa sponsorship: Yes, we sponsor visas.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nWe’re using AI-driven simulation to solve hard physical process optimization problems in advanced manufacturing. As a forward deployed engineer focused on physics and simulation, you will be the technical backbone of our most demanding customer engagements – spending significant time on-site, embedding directly with customer teams, and owning simulation workflows end-to-end.\n\nYou’ll work with our modeling and ML teams to build and calibrate physics-based simulations, turn customer process knowledge into computational models, and drive recipe optimization with direct feedback loops to production. This is a hands-on, high-ownership role at the frontier of AI for physical science.\n\nThis role requires travel to and extended time on-site in Taiwan.\n\n\n\n\nWHAT YOU’LL DO\n\n - Own the simulation workflow end-to-end for customer engagements, from model setup and calibration through optimization and results interpretation\n\n - Run, debug and modify physics-based simulations of complex physical processes in diverse domains, such as microfluidics, charge transport and structural deformation\n\n - Work on-site with customer engineering teams on-site to understand process constraints, interpret simulation results into real process improvements\n\n - Write tools, skills and agents to reliably drive end-to-end LLM-based simulation workflows, including experimental validation, parameter fitting and recipe optimization\n\n - Build and extend simulation tooling in Python – job submission, parameter sweeps, output parsing, integration\n\n - Feed domain insights back to the research and product teams, shaping the next version our platform\n \n \n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - A strong foundation in numerical simulation of continuum systems – fluid dynamics, heat transfer, structural mechanics, electromagnetics, or similar – gained through graduate research, industry, or both\n\n - Hands-on experience solving partial differential equations numerically, including mesh generation, solver tuning, and debugging numerical instabilities\n\n - Solid Python skills for scripting and scientific computing (NumPy, SciPy, or similar)\n\n - A process engineer’s instinct: you treat simulations as tools for answering real process questions, not just jobs to run\n\n - Strong communication skills and genuine comfort working directly with customer engineers\n\n - Willingness to spend extended periods on-site in Taiwan\n\n - A self-starter mindset: you can take a technical problem from definition to deployed result without much hand-holding\n \n \n\n\nESPECIALLY STRONG CANDIDATES MAY ALSO HAVE\n\n - CFD background, including tools like OpenFOAM, ANSYS Fluent, Star-CCM+, or custom solvers\n\n - Grad-level research experience building simulation software in domains like mechanical or chemical engineering, weather modeling, astrophysics, or materials processing\n\n - Familiar with semiconductor manufacturing processes\n\n - Familiarity with physics-informed ML, surrogate modeling, or neural operators applied to simulation acceleration\n\n - Experience integrating simulation tools into larger software platforms or automated optimization pipelines\n\n - Mandarin proficiency for on-site collaboration in Taiwan\n\n - Lab or experimental background, with an appreciation for how simulation connects to physical data\n \n \n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA (Soon: San Francisco, too) + frequent travel to Taiwan\n\nCompensation: $200,000-$275,000 + equity\n\nVisa sponsorship: Yes, we sponsor visas."},{"id":"b1ad8632-f489-4922-8805-42d84711cda1","title":"Laboratory Operations & Maintenance Technician","department":"Science","team":"Science","employmentType":"Contract","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-06-11T16:55:25.789+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/b1ad8632-f489-4922-8805-42d84711cda1","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/b1ad8632-f489-4922-8805-42d84711cda1/application","descriptionHtml":"We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
Periodic Labs is building an autonomous laboratory for high-throughput materials discovery — combining advanced synthesis, characterization, automation, robotics, and AI to accelerate the development of next-generation materials. We're looking for a highly capable, hands-on Laboratory Operations & Maintenance Technician to help build, maintain, and scale the physical infrastructure that enables our scientific and engineering teams to move quickly.
This is an ideal role for someone who enjoys solving practical problems, working with tools, building systems, troubleshooting equipment, and taking ownership of laboratory operations. You'll work across equipment maintenance, gas and vacuum systems, utilities, instrumentation, automation support, machine shop operations, inventory management, and laboratory buildout projects.
Equipment Maintenance & Reliability
Execute preventative maintenance programs for laboratory equipment using MaintainX CMMS; develop and improve maintenance procedures, inspection checklists, and work order templates
Perform routine inspections, cleaning, calibration checks, and equipment upkeep across mechanical, electrical, pneumatic, gas, vacuum, and fluid handling systems
Take initiative to troubleshoot to component level and repair equipment; identify recurring failure modes and implement corrective actions to improve uptime
Coordinate service visits and maintenance activities with equipment vendors
Service vacuum pumps, cooling water systems, chillers, and associated infrastructure; verify equipment meets OEM specifications after maintenance or repairs
Asset Management & Documentation
Maintain an accurate asset registry within MaintainX, including equipment records (manuals, schematics, service histories, serial numbers, manufacturer contacts)
Label equipment with asset numbers and QR codes; update equipment layouts, utility matrices, and infrastructure documentation
Track maintenance history and equipment performance metrics
Utilities & Infrastructure
Maintain laboratory utility systems including compressed gases, vacuum systems, process cooling water, exhaust systems, gas detection, and general lab infrastructure
Build and modify gas and fluid handling systems from P&IDs and engineering drawings; assemble and install tubing, regulators, valves, gauges, sensors, and associated hardware
Support utility capacity planning and identify infrastructure constraints
Equipment Installation & Commissioning
Support installation and startup of new laboratory equipment; coordinate utility hookups including power, water, gas, vacuum, and networking
Procure and install supporting infrastructure including tubing, fittings, pumps, sensors, regulators, and instrumentation
Perform installation verification and commissioning activities; document as-built configurations and equipment changes
Automation & Controls Support
Support Controls and Automation Engineers with equipment integration projects
Install and maintain thermocouples, RTDs, pressure transducers, flow meters, solenoid valves, gas sensors, and safety interlocks
Route, terminate, and label instrumentation and communication wiring; assist with sensor replacement, control panel modifications, and field troubleshooting
Machine Shop & Fabrication
Fabricate fixtures, brackets, guards, adapters, and experimental hardware using drill press, band saw, chop saw, belt sander, bench grinder, manual mill, and manual lathe
Modify commercial components and support custom equipment builds; maintain machine shop organization and tooling
Inventory & Laboratory Operations
Maintain inventories of spare parts, maintenance consumables, PPE, and laboratory supplies; identify critical spare parts and establish appropriate stock levels
Receive and organize incoming equipment, chemicals, gases, and supplies; register chemicals and gas cylinders within laboratory inventory systems
Coordinate gas cylinder replacement and deliveries; support hazardous waste staging and disposal activities
Assist with laboratory organization, equipment moves, and expansion projects
Safety & Compliance
Perform all work in accordance with laboratory safety procedures and LOTO requirements; participate in routine safety inspections and identify unsafe conditions
Support safe installation and modification of laboratory equipment and infrastructure
Maintain clean, organized, and professional workspaces; use all appropriate PPE (lab coats, gloves, safety glasses, hearing protection, respirators)
5+ years of experience in laboratory operations, manufacturing, semiconductor, chemical processing, pilot plant, industrial maintenance, or a related environment
The ability to read and interpret P&IDs, mechanical drawings, electrical wiring diagrams, and equipment manuals
Strong hands-on experience with hand tools, power tools, and mechanical assembly, with excellent troubleshooting and problem-solving skills
An associate degree, technical certification, military technical training, trade apprenticeship, or equivalent hands-on experience
Comfort operating in a fast-paced, dynamic startup environment with shifting priorities
Swagelok tubing, fitting, and tube bending experience; gas manifold assembly from P&IDs
Vacuum systems and/or compressed gas systems experience
Semiconductor equipment maintenance experience
Electrical troubleshooting down to PCB/component level using multimeters
MaintainX or other CMMS experience
Forklift or material handling equipment experience
Handling of hazardous chemicals & laboratory operations experience
Process piping and instrumentation experience
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA
Compensation: $100,000 - $140,000
Visa sponsorship: No, sorry we are not able to sponsor visas at this time.
We're building a team of the world's best — the scientists, engineers, and problem-solvers who don't just follow the frontier, they define it. If you're driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
","descriptionPlain":"ABOUT PERIODIC LABS\n\nWe're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.\n\n\n\n\nABOUT THE ROLE\n\nPeriodic Labs is building an autonomous laboratory for high-throughput materials discovery — combining advanced synthesis, characterization, automation, robotics, and AI to accelerate the development of next-generation materials. We're looking for a highly capable, hands-on Laboratory Operations & Maintenance Technician to help build, maintain, and scale the physical infrastructure that enables our scientific and engineering teams to move quickly.\n\nThis is an ideal role for someone who enjoys solving practical problems, working with tools, building systems, troubleshooting equipment, and taking ownership of laboratory operations. You'll work across equipment maintenance, gas and vacuum systems, utilities, instrumentation, automation support, machine shop operations, inventory management, and laboratory buildout projects.\n\n\n\n\nWHAT YOU'LL DO\n\nEquipment Maintenance & Reliability\n\n - Execute preventative maintenance programs for laboratory equipment using MaintainX CMMS; develop and improve maintenance procedures, inspection checklists, and work order templates\n\n - Perform routine inspections, cleaning, calibration checks, and equipment upkeep across mechanical, electrical, pneumatic, gas, vacuum, and fluid handling systems\n\n - Take initiative to troubleshoot to component level and repair equipment; identify recurring failure modes and implement corrective actions to improve uptime\n\n - Coordinate service visits and maintenance activities with equipment vendors\n\n - Service vacuum pumps, cooling water systems, chillers, and associated infrastructure; verify equipment meets OEM specifications after maintenance or repairs\n\nAsset Management & Documentation\n\n - Maintain an accurate asset registry within MaintainX, including equipment records (manuals, schematics, service histories, serial numbers, manufacturer contacts)\n\n - Label equipment with asset numbers and QR codes; update equipment layouts, utility matrices, and infrastructure documentation\n\n - Track maintenance history and equipment performance metrics\n\nUtilities & Infrastructure\n\n - Maintain laboratory utility systems including compressed gases, vacuum systems, process cooling water, exhaust systems, gas detection, and general lab infrastructure\n\n - Build and modify gas and fluid handling systems from P&IDs and engineering drawings; assemble and install tubing, regulators, valves, gauges, sensors, and associated hardware\n\n - Support utility capacity planning and identify infrastructure constraints\n\nEquipment Installation & Commissioning\n\n - Support installation and startup of new laboratory equipment; coordinate utility hookups including power, water, gas, vacuum, and networking\n\n - Procure and install supporting infrastructure including tubing, fittings, pumps, sensors, regulators, and instrumentation\n\n - Perform installation verification and commissioning activities; document as-built configurations and equipment changes\n\nAutomation & Controls Support\n\n - Support Controls and Automation Engineers with equipment integration projects\n\n - Install and maintain thermocouples, RTDs, pressure transducers, flow meters, solenoid valves, gas sensors, and safety interlocks\n\n - Route, terminate, and label instrumentation and communication wiring; assist with sensor replacement, control panel modifications, and field troubleshooting\n\nMachine Shop & Fabrication\n\n - Fabricate fixtures, brackets, guards, adapters, and experimental hardware using drill press, band saw, chop saw, belt sander, bench grinder, manual mill, and manual lathe\n\n - Modify commercial components and support custom equipment builds; maintain machine shop organization and tooling\n\nInventory & Laboratory Operations\n\n - Maintain inventories of spare parts, maintenance consumables, PPE, and laboratory supplies; identify critical spare parts and establish appropriate stock levels\n\n - Receive and organize incoming equipment, chemicals, gases, and supplies; register chemicals and gas cylinders within laboratory inventory systems\n\n - Coordinate gas cylinder replacement and deliveries; support hazardous waste staging and disposal activities\n\n - Assist with laboratory organization, equipment moves, and expansion projects\n\nSafety & Compliance\n\n - Perform all work in accordance with laboratory safety procedures and LOTO requirements; participate in routine safety inspections and identify unsafe conditions\n\n - Support safe installation and modification of laboratory equipment and infrastructure\n\n - Maintain clean, organized, and professional workspaces; use all appropriate PPE (lab coats, gloves, safety glasses, hearing protection, respirators)\n\n\nYOU WILL THRIVE IN THIS ROLE IF YOU HAVE\n\n - 5+ years of experience in laboratory operations, manufacturing, semiconductor, chemical processing, pilot plant, industrial maintenance, or a related environment\n\n - The ability to read and interpret P&IDs, mechanical drawings, electrical wiring diagrams, and equipment manuals\n\n - Strong hands-on experience with hand tools, power tools, and mechanical assembly, with excellent troubleshooting and problem-solving skills\n\n - An associate degree, technical certification, military technical training, trade apprenticeship, or equivalent hands-on experience\n\n - Comfort operating in a fast-paced, dynamic startup environment with shifting priorities\n\n\nESPECIALLY STRONG CANDIDATES SHOULD HAVE\n\n - Swagelok tubing, fitting, and tube bending experience; gas manifold assembly from P&IDs\n\n - Vacuum systems and/or compressed gas systems experience\n\n - Semiconductor equipment maintenance experience\n\n - Electrical troubleshooting down to PCB/component level using multimeters\n\n - MaintainX or other CMMS experience\n\n - Forklift or material handling equipment experience\n\n - Handling of hazardous chemicals & laboratory operations experience\n\n - Process piping and instrumentation experience\n\n\nMECHANICS\n\nMinimum education: Bachelor’s degree or similar experience\n\nLocation: Menlo Park, CA\n\nCompensation: $100,000 - $140,000\n\nVisa sponsorship: No, sorry we are not able to sponsor visas at this time.\n\nWe're building a team of the world's best — the scientists, engineers, and problem-solvers who don't just follow the frontier, they define it. If you're driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here."},{"id":"c4e0774f-0f3e-4ea7-be27-fb89130c0d01","title":"Research Scientist/Research Engineer, Materials Data","department":"Science","team":"Science","employmentType":"FullTime","location":"Menlo Park, CA","secondaryLocations":[],"publishedAt":"2026-09-01T19:03:08.269+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Menlo Park"}},"jobUrl":"https://jobs.ashbyhq.com/periodic-labs/c4e0774f-0f3e-4ea7-be27-fb89130c0d01","applyUrl":"https://jobs.ashbyhq.com/periodic-labs/c4e0774f-0f3e-4ea7-be27-fb89130c0d01/application","descriptionHtml":"About Periodic Labs
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
About the Role
At Periodic Labs, we are automating scientific research in materials discovery; the data we collect, and how we represent it, is what makes this possible. We are hiring a materials scientist to work across the entire process: to find where our agents and data fail, and to fix those failures at the source. This is a hybrid research and infrastructure role. Roughly half your time will be spent working directly with our experimental and computational scientists, building agents and tools that solve active research problems. The other half will be spent improving the data those agents depend on.
This role requires domain depth, not just data engineering skill. You need to know, for example, what metadata actually matters for a given characterization technique. The research half of the role keeps you grounded in the problems we are actually using LLMs to solve, so the schemas you build serve real research rather than an abstraction of it. The work demands attention to detail and a willingness to get into the weeds: to meticulously read, understand, and improve our data. You'll be as much a materials scientist doing research as the person who makes our agentic harness actually work.
What You'll Do
Work directly with lab scientists and the computational team on active research problems, staying close to the actual bottlenecks LLM agents are meant to solve.
Investigate agent traces to identify data errors and agentic failure modes, and eliminate them at the source.
Restructure and re-architect our materials databases (lab experiments, characterization data, computations) around how LLM agents actually reason and fail, not just around human readability. Draw on domain expertise about how to represent the data and what metadata matters.
Work with the hardware and automation teams to make data collection more robust.
Build research software for lab environments, translating scientific requirements into working tools.
Distill what you learn into evaluations that measure agent performance.
Mechanics
Minimum experience: 4+ years of research or industry experience in experimental or computational materials science and working with data at scale.
Minimum education: PhD in Materials Science, Chemistry, or a related field, or equivalent industry experience.
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $250,000-350,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re looking for a senior, versatile recruiter to join our lean team. You’ll partner closely with hiring managers and company leadership to own searches from kickoff through close. This is a hands-on role for someone who is independent, proactive, and enjoys operating with a high degree of ownership in a fast-moving environment.
What You'll Do
Partner with hiring managers and executives to define hiring strategies and run searches end-to-end.
Source, assess, and close candidates across technical and non-technical roles.
Build strong relationships with candidates and guide them through a high-quality hiring experience.
Continuously improve our recruiting processes and jump in wherever needed.
You Will Thrive in This Role If You Have
Significant experience owning full-cycle recruiting with minimal oversight.
A track record of closing candidates against strong competing offers.
Strong judgment, clear communication, and the ability to build trust with candidates, hiring managers, and executives.
A proactive mindset - you identify what needs to be done and take initiative without being asked.
Experience recruiting in the semiconductor industry is a plus.
Minimum experience: 5 years
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $175,000-$275,000 base + equity
Periodic Labs is building an autonomous laboratory for high-throughput materials discovery. Our work combines advanced chemistry, robotics, automation, AI, and materials science to accelerate scientific discovery while maintaining high standards of environmental, health, and process safety.
We are seeking a hands-on, highly organized EHS Technician to support day-to-day laboratory safety operations, hazardous waste management, chemical inventory, compliance activities, and laboratory readiness.
Working closely with the EHS Engineer, Facilities team, scientists, and technicians, you will help execute the laboratory’s EHS programs and keep the facility safe, compliant, organized, and inspection-ready.
Receive, inspect, label, inventory, and properly store incoming chemicals and compressed gases.
Maintain accurate chemical inventory, SDS, hazard classification, and storage-location records in the laboratory inventory or LIMS system.
Monitor chemical, compressed-gas, PPE, spill-response, and other EHS supply inventories and reorder as needed.
Collect, label, package, move, and stage hazardous waste, including flammable solvents, corrosives, toxic and heavy-metal waste, pyrophoric and reactive waste, universal waste, electronic waste, sharps, used oil, vacuum pump oil, and contaminated PPE.
Change satellite waste containers and support handling of larger containers, including 55-gallon drums, using approved procedures and equipment.
Maintain satellite and central accumulation areas, ensuring containers are closed, compatible, properly labeled and dated, and managed within applicable storage limits.
Coordinate hazardous waste pickups with disposal vendors and maintain manifests, profiles, disposal records, and related documentation.
Perform routine laboratory safety inspections and compliance audits; document findings, assign or track corrective actions, and verify closure.
Inspect and maintain spill kits, eyewash stations, safety showers, first aid supplies, fire extinguishers, oxygen monitors, gas detection equipment, PPE stations, emergency signage, and evacuation routes.
Support gas detector bump testing, calibration coordination, maintenance records, and user training.
Coordinate EHS onboarding, required safety training, respirator medical evaluations and fit testing, and other employee safety programs.
Support regulatory, fire department, insurance, and internal inspections, including preparation of records and follow-up actions.
Collect wastewater, process water, air, wipe, or other environmental samples and coordinate testing with external laboratories.
Support chemical inventory reconciliation, CERS reporting, regulatory documentation, laboratory cleanouts, equipment moves, shutdowns, and decommissioning.
Maintain strong laboratory housekeeping and proactively identify safety, storage, labeling, or compliance issues before they affect operations.
Associate degree, technical certification, bachelor’s degree, or equivalent experience in EHS, chemistry, environmental science, occupational health, industrial technology, or a related field.
At least 1–2 years of experience in laboratory operations, hazardous waste, chemical management, industrial EHS, semiconductor, biotechnology, manufacturing, or a related technical environment.
Familiarity with laboratory chemical handling, hazard compatibility, and hazardous waste management.
Strong organizational skills, attention to detail, and comfort maintaining accurate records.
Able to safely move containers, handle supplies, and work throughout an active laboratory environment.
Comfortable working independently while coordinating closely with scientists, engineers, vendors, and regulators.
Experience with RCRA and California hazardous waste requirements, including DTSC, CUPA, or CERS.
Experience with chemical inventory systems, environmental sampling, DOT hazardous-materials requirements, or TSDF coordination.
HAZWOPER, CPR/First Aid, forklift, pallet jack, or related safety training.
Experience supporting semiconductor, advanced materials, chemical, or research laboratories.
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA
Compensation: $96,000-$124,000 + equity
About Periodic Labs
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
About the Role
As a Research Engineer, Semiconductor, you’ll own device-level validation of our materials work, taking novel thin-film stacks from deposition through patterned test vehicles to measure electrical performance. You’ll design and run short-loop experiments that demonstrate how materials and interfaces translate into device behavior, leveraging both internal and external lab resources. You’ll also contribute technical expertise to customer-facing engagements, and this role blends deep hands-on capability with the flexibility to work across teams and partners to solve hard materials problems.
What You’ll Do
Design, fabricate, and characterize short-loop device test vehicles that demonstrate material and device performance against clear electrical targets.
Build patterned devices end-to-end using photolithography, direct-write laser lithography, or e-beam lithography, integrated with deposition, etch, and metrology.
Deposit thin-film stacks with engineered, complex interfaces using PVD, PLD, MBE, and ALD/CVD techniques.
Perform electrical characterization on probe stations, and design and build custom measurement test benches where commercial tools fall short.
Connect materials and interface properties to device outcomes, feeding insights back into film-stack and process development.
Contribute technical expertise to customer-facing engagements, translating customer needs into experimental plans and results.
Document experimental methodology, results, and learnings to feed both internal knowledge and AI training infrastructure.
You Will Thrive in This Role If You Have
MS or PhD in Materials Science, Electrical Engineering, Physics, or a related field, plus relevant industry experience.
Semiconductor industry experience in device development or process integration, background at an IDM, foundry, or memory manufacturer strongly preferred.
Strong command of device physics and integration flows, with a track record of demonstrating device performance in short-loop test vehicles.
Hands-on fabrication experience spanning lithography (photo, laser direct-write, or e-beam), thin-film deposition, etch, and metrology.
A deep understanding of how materials selection and interface quality drive device performance.
Proficiency in probe-station device measurement, plus the ability to architect and assemble custom electrical test setups.
A strong condensed matter physics foundation, spintronics, magnetic materials, or quantum phenomena, is a plus.
Working knowledge of emerging memory and logic device architectures is a plus.
Startup-ready mindset: able to operate effectively in a fast-paced, ambiguous environment while implementing industry-standard best practices.
Mechanics
Minimum education: Master’s degree with relevant experience
Location: Menlo Park, CA
Compensation: $220k - $300k + equity
Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process with our legal support.
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
Join a tight-knit engineering team building the integrated lab systems that scale our materials synthesis and characterization, alongside our frontier models, scientific data, and the scientists who use them.
Periodic Labs is seeking a Mechanical Engineer to help build the environment where materials scientists work alongside AI agents to plan experiments, run analyses, coordinate workflows, and turn results into decisions. You'll work with the team to translate vague, early-stage problems from scientists and engineers into clear requirements and build-ready hardware, owning the mechanical design of lab systems and instrumentation end to end and seeing them through fabrication, assembly, and operational bring-up.
This role will help define what engineering looks like at Periodic: technically deep, ambitious in scope, and tightly coupled to scientific work.
Collaborate with a multidisciplinary team of materials scientists and engineers to synthesize vague, early-stage problems into clear requirements and hardware that solves them.
Own the design and build of systems and subsystems for lab automation and workflows, from concept through installation.
Layout and design core lab systems, including gloveboxes, furnaces, presses, deposition equipment, and consumables.
Design and customize lab machines and instrumentation to fit evolving scientific needs.
Program and troubleshoot robots integrated into lab workflows.
Engage directly with scientists and technicians to understand how they actually work, getting past stated requirements to uncover the real needs behind them, and translate that into clear engineering specifications.
Produce CAD, mechanical drawings and design documentation, including GD&T, to support both in-house builds and subcontracted manufacturing.
Assemble and build hardware hands-on, and manage subcontracted manufacturing across machining, additive, sheet metal, and welding.
Apply a strong safety mindset throughout design and build, with attention to engineering and process controls.
2+ years of mechanical design experience, with hands-on and vendor-facing manufacturing exposure (machining, additive, sheet metal, welding).
Proficiency in CAD (Onshape or equivalent) and hand calculations.
Demonstrated ability to discover and write clear requirements, with strong project ownership from concept to completion.
Experience assembling and building physical hardware, not just designing it on paper.
Comfort working closely with scientists and technicians to translate workflow needs into engineering requirements and real hardware that solves problems.
Experience programming and controlling robots or other automated lab systems.
Experience working in software repos with agentic collaboration.
Experience dispensing challenging materials.
Measurement and test experience.
Design experience for high-temperature service.
Experience with test planning and bring-up.
Minimum experience: 2+ years
Minimum education: Bachelor's degree or similar experience
Location: Menlo Park, CA
Compensation: $200,000-$300,000 + equity
Visa sponsorship: Yes, we sponsor visas
Periodic Labs is building an autonomous laboratory for high-throughput materials discovery. Our work combines advanced chemistry, robotics, automation, AI, and materials science to accelerate scientific discovery while maintaining high standards of environmental, health, and process safety.
We are seeking a hands-on, I&C technician who enjoys working with materials, instrumentation, electro-/mechanical systems, and characterization tools - someone who values precision, documentation, and evolving lab processes.
Provide electrical, instrumentation, and controls technician support to lead engineers, scientific, and technical staff, utilizing hand and CAD tools where design parameters and specifications have been established
Build and manage large, complex electrical CAD assemblies for custom electrical equipment and fixtures, electrical enclosures, and instrumentation/hardware from engineer-provided concepts, sketches, and verbal direction
Perform interference checks, fit studies, and assembly verification to identify issues before fabrication
Produce detailed 2D engineering drawings with geometric dimensioning and tolerancing
Generate accurate bills of materials (BOMs), drawing packages, cut sheets, and RFQ-ready documentation to support procurement and fabrication
Perform basic calculations using standard engineering formulas to support dimensioning, fitment, and material selection
Interpret electrical drawings and other technical information
Maintain systems documentation, bill-of-materials, and drawing archives to keep documentation current, visible, and traceable
Manage CAD file organization, naming conventions, and revision control
Incorporate redlines and design changes from engineers, updating models and drawings through revision cycles
Qualifications & Skills
Required:
Bachelor’s degree (or equivalent lab experience) in Materials Science, Physics, Chemistry, Electrical Engineering, Control Systems, or related field (or strong background in mechatronics, electronics, solid‑state, materials processing, inorganic chemistry)
Hands‑on instrumentation & controls experience, preferably low-voltage (24VDC) wiring and controls enclosure fabrication
Experience in wiring and integrating mass flow controllers (MFCs), pressure transducers, solenoid valves, thermocouples, and various control instrumentation and hardware
Familiarity with AutoCAD (preferably electrical), redlining schematics, and building to print
Experience selecting appropriate electrical supplies, wire/cable, enclosure components (e.g. relays, circuit-breakers, terminal blocks)
Experience with digital multi-meters (DMMs), volt meters, and current measuring devices
Experience with Lock-Out-Tag-Out (LOTO) safety practices and procedures
Strong attention to detail, record‑keeping, and job/task documentation
Comfort with physically wiring various digital and analog input/output devices, lab instrumentation, and controls fieldbuses (e.g., EtherCAT, RS-232/-485, Modbus)
Good documentation skills, ability to follow protocols, and write clear notes/task summaries
Flexibility and ability to adapt to evolving processes and workflows typical of a startup/ research‑oriented lab
Experience with superconducting / magnetic materials, cryogenic sample handling, and magnetometry or resistivity measurements
Experience with vacuum systems, gloveboxes, and inert atmosphere processing
Familiarity with lab automation, data logging, or LIMS/LES systems integration
Comfort troubleshooting instruments or basic electro-/mechanical maintenance
Familiarity with NFPA70 (NEC), UL508A, or NFPA79
Familiarity with Beckhoff IPCs, input/output modules, and EtherCAT fieldbus
Familiarity with ASME Y14.5 standards
What You’ll Gain
Hands‑on experience working at the cutting edge of materials discovery (superconductors, novel compounds)
Exposure to a broad set of material characterization techniques and workflows (from synthesis to cryogenic measurements)
Opportunity to help build lab SOPs, workflows, and influence lab design and automation controls development/deployment strategy
Collaborative environment with scientists, engineers, and automation experts — good learning and growth potential
Satisfaction of bridging materials science, synthesis, measurement, and data-driven R&D
Hands-on experience designing, fabricating, and troubleshooting cutting-edge electrical systems for laboratory instrumentation and automation
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA
Compensation: The annual compensation range for this role is $124,000-$153,600
Role Type: Full-time / Contractor
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and a drive to push the boundaries of what's scientifically possible.
We're training frontier models to develop deep scientific knowledge and reasoning for scientific discovery. As a Midtraining Research Engineer, you'll take base models and improve their scientific reasoning: curating and generating data, building evals, and running large-scale training experiments. Your work will also lay the groundwork for our pre-training efforts down the line.
Identify, process, and curate novel sources of scientific data for large-scale model training.
Generate high-quality synthetic data to fill gaps in scientific knowledge and reasoning.
Build evaluations that correlate with downstream scientific task performance, working closely with RL researchers, physicists, and chemists.
Develop and apply techniques such as self-distillation and on-policy distillation to improve model capability.
Design and run large-scale training experiments, partnering with supercompute engineers to scale efficiently across thousands of GPUs.
Build tools for yourself and the team to investigate how data choices shape model intelligence.
Experience training LLMs on curated mixes of trillions of tokens.
Experience on a dedicated evals team supporting a large production training run.
Hands-on use of self-distillation, on-policy distillation, or similar methods in a real training pipeline.
Experience with scaling laws and compute-optimal hyperparameters.
Comfort working across data, evals, and training infrastructure.
Experience optimizing throughput and reliability for large-scale distributed training runs.
A background in AI for science or training on specialized domain data (e.g., protein, materials, or other scientific datasets).
Experience creating evals or synthetic data for non verifiable tasks and tracking performance over live runs.
Minimum education: Bachelor's degree or similar experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $250,000–$350,000 + equity
Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.
Periodic Labs is building an autonomous laboratory for high-throughput materials discovery. Our work combines advanced chemistry, robotics, automation, AI, and materials science to accelerate scientific discovery while maintaining high standards of environmental, health, and process safety.
About the Role
Periodic Labs is building AI that can both simulate science and verify its own predictions. Verifying those predictions experimentally requires a lab that runs reliably - qualified tools, samples prepared to spec, and data logged the same way every time.
We are standing up a dedicated thin-film lab in Menlo Park with a suite of deposition and characterization tools, and are hiring a Process Technician to own day-to-day tool operation, sample preparation, and first-line maintenance. This is the role that keeps throughput high and variance low: you run the SOPs, you cut and prep the coupons, you keep the tools in spec, and you partner with process engineers when an experiment calls for something outside the standard flow.
This is a contract position, on-site, with the possibility of extension or conversion as the lab scales.
What You'll Do
Run deposition tools to SOP. Execute recipes on vacuum-based thin-film deposition systems. Load and unload, verify chamber state and process conditions, confirm the run matched setpoints, and log the result.
Prepare samples. Dice and cleave coupons from full wafers; handle mounting and cross-section prep for imaging. Clean and prep substrates per workflow-specific recipes — wet cleans, oxide strip, dehydration bake, substrate and source conditioning.
Operate characterization tools. Collect and log structural, optical, and electrical film data. Recognize when a scan, fit, or image indicates a tool problem rather than a material result, and escalate rather than re-run blind.
Perform first-line and preventive maintenance. Chamber opens and cleans, source and consumable changes, shield and liner swaps, pump-down and leak checks, calibration checks, and PM scheduling. Work with vendors and facilities on service visits and keep maintenance history complete.
Keep the tools qualified. Run qual and monitor samples on a set cadence, track thickness, uniformity, and rate against baseline, and flag drift early. Maintain SPC-style charts where they exist and help build them where they don't.
Support non-standard work. When engineers need a one-off — an unusual stack, an off-recipe parameter sweep, a new substrate geometry, an unproven prep sequence — you help scope what the tool can safely do, run it, and document what actually happened.
Document everything. Every run is a potential data point for our models. Record what you did rather than what the recipe said, capture failures and fixes alongside successes, and meet the metadata standards our data pipeline depends on.
Own lab safety and housekeeping. Chemical handling and waste, gas and precursor changes, lockout/tagout, cleanroom protocol and gowning discipline, and spares and consumables inventory - including at partner facilities we use during ramp.
You Will Thrive in This Role If You Have
3+ years of hands-on experience operating thin-film deposition and/or metrology equipment in a semiconductor fab, R&D line, or equipment supplier environment. You have spent real time at a tool, not adjacent to one.
Working knowledge of at least one deposition technique at the level of practical detail: what a bad pump-down looks like, when a source needs conditioning, why a recipe that ran fine last week is now off-rate.
Sample prep skill with delicate materials — dicing or cleaving, mounting, cross-sectioning, and cleaning without introducing artifacts.
Comfort with basic metrology data: reading a thickness map, sanity-checking a film measurement, spotting delamination or particles in an image.
Mechanical aptitude and hands-on maintenance instinct. You are comfortable inside a chamber, with fittings and fasteners, and with following a service procedure precisely.
Rigorous documentation habits and attention to detail. You understand why \"what I intended\" and \"what I did\" are different records.
Cleanroom experience and full respect for protocol, chemical safety, and contamination control.
The ability to work independently, prioritize across several engineers' requests, and escalate anomalies early.
Especially Strong Candidates May Also Have
Associate degree or technical certificate in a related field, or equivalent military or industry training.
Experience in a high-mix, low-volume R&D environment where the recipe changes daily and no two lots are identical.
Vacuum system troubleshooting, RF matching and plasma tuning, or mass flow and pressure control calibration.
Experience with LIMS, MES, or other systems for tracking samples, runs, and characterization results, and the instinct to treat logging as part of the experiment.
Wafer-level metrology experience: thickness and resistivity mapping, stress and warpage, at wafer scale rather than coupon scale.
Familiarity with in-situ or real-time process monitoring during deposition.
Prior work at university nanofabrication facilities or shared cleanrooms, including facility safety training and tool reservation systems.
Mechanics
Engagement type: Contract position. Initial term of 6 months with potential to extend or convert based on lab needs and performance
Minimum education: High school diploma or equivalent, plus relevant hands-on experience; technical degree or certificate preferred
Location: On-site in Menlo Park, CA
Schedule: Standard weekday shift, with occasional flexibility for tool PM windows, vendor installs, or time-critical experiments
Compensation: $45-$65 per hour
Work authorization: Must be authorized to work in the U.S. for the duration of the contract. Visa sponsorship is not available for this position
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
About the Role
Join our team of scientists and engineers building a lab where AI and automation speed up materials discovery.
We're building an autonomous lab to speed up materials discovery, and we need someone who understands materials R&D from the inside — someone who's run the experiments, fought with the instruments, and knows what \"the workflow\" actually means at the bench. As our Research Engineer, you'll work directly with scientists to understand what they're trying to learn, then translate that into the hardware setups, instrument sequences, and engineering requirements that make it possible to automate.
What You'll Do
Work closely with bench scientists to understand experimental goals and turn them into concrete hardware and workflow requirements.
Evaluate, select, and configure lab instrumentation and hardware to support new and existing materials R&D workflows.
Design experimental and automation workflows that hold up to the realities of materials synthesis and characterization.
Serve as the technical bridge between scientists and the automation/software engineering team, making sure integration specs reflect how the science actually works.
Troubleshoot instrument and workflow issues that require materials domain knowledge to diagnose.
Collaborate with AI and data scientists to help shape how experimental data is structured and used for analysis and planning.
You Will Thrive in This Role If You Have
PhD in Materials Science, Chemistry, Chemical Engineering, or a related field (or equivalent research experience).
Strong working knowledge of common materials lab hardware (e.g. furnaces, fluid/gas handling manifolds, characterization tools, synthesis equipment) and the workflows built around them.
Ability to communicate fluently with both scientists and engineers, and to translate scientific intent into clear technical requirements.
Comfort writing Python to interact with instruments, manipulate experimental data, and prototype automation workflows
Especially Strong Candidates May Also Have
Prior experience working alongside automation or software engineers.
Experience with electronic lab notebooks, LIMS, or other lab data systems.
A track record of designing or adapting experimental protocols for higher-throughput or automated execution.
Mechanics
Minimum education: PhD or equivalent combination of education and hands-on research experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $200,000-$250,000 + equity
Visa sponsorship: Yes, we sponsor visas.
Periodic Labs is an AI and physical sciences company in Menlo Park, CA. We run an in-house materials synthesis and characterization lab alongside our research teams.
We are looking for an experienced diffraction specialist to manage our X-ray diffraction facility, which includes multiple laboratory diffractometers used for powder, thin-film, and capillary measurements. You will be responsible for instrument alignment and calibration, preventive maintenance and repair, user training, measurement standards, radiation safety, and overall attention to the performance of the X-ray equipment.
You will also help specify and commission new instruments, write the SOPs and qualification protocols the group works from, and work with our software team so that instrument data and metadata are recorded consistently. You will work daily with scientists, technicians, and engineers across synthesis, software, and research.
Instrument alignment, calibration, configuration control, and uptime across the facility, including the criteria used to decide whether an instrument is ready for use.
Reference standards and quality control: maintain house standards and a regular QC schedule so that the same standard gives consistent results across instruments
Difficult measurements: non-routine geometries, weakly scattering or air-sensitive samples, thin films, and non-ambient stages, with attention to distinguishing instrument artifacts from real effects.
Maintenance and repair: troubleshooting and preventive maintenance; coordination of service contracts and vendor visits when needed.
Commissioning new instruments: site preparation, acceptance testing, and comparison against existing instruments.
User training: train and certify scientists and technicians, review early runs, and provide support.
Documentation and data: maintain SOPs, measurement recipes, and data-reduction conventions; ensure raw data, instrument state, calibration status, and sample metadata are recorded consistently and in a structured format.
Radiation safety: X-ray equipment registration and compliance, interlock testing, surveys, along with compressed gas and cryogen handling for non-ambient stages.
5+ years of hands-on experience operating and maintaining X-ray diffractometers in a university shared facility, national lab, analytical services lab, industrial R&D lab, or at an instrument vendor.
Strong XRD background across powder, thin-film, and capillary/transmission work. Proficient in phase identification, Rietveld refinement, and quantitative analysis.
Experience maintaining several instruments, ideally from more than one vendor. Comfortable troubleshooting hardware and judging when to repair versus call for service.
Careful documentation habits; treats metadata as part of the measurement.
Able to support many users in a busy lab while maintaining good practice.
PhD in materials science, physics, chemistry, or a related field, or equivalent experience.
Preferred: experience managing a shared user facility or commercial XRD lab, automation, or other materials characterization techniques.
Type: Full-time
Location: On-site in Menlo Park, CA.
Schedule: Standard weekday schedule.
Compensation: 200k-275k plus equity, commensurate with experience.
Work authorization: [Must be authorized to work in the U.S. / Visa sponsorship available for exceptional candidates.]
About Periodic Labs
We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
About the Role
As an Equipment Engineer, you will own the commissioning, qualification, and maintenance of the vacuum and deposition hardware that powers our AI-accelerated thin-film and semiconductor processing lab. You will commission, qualify, and maintain R&D thin-film deposition systems, including but not limited to PVD, CVD, and ALD, working closely with vendors to assemble, install, and bring tools online, and troubleshoot complex vacuum and process-hardware issues at the equipment level.
You will also be hands-on in bringing up new tools and reactors, integrating in-situ characterization and metrology capabilities, writing equipment specifications and SOPs, and working closely with vendors to procure and qualify capital equipment. In this role, you will collaborate daily with internal teams spanning AI/ML, simulation, process engineering, and physics/chemistry to stand up scalable lab infrastructure for high-value problems.
What You'll Do
Lab Development: Contribute to the buildout and scale-up of an AI-accelerated thin-film and semiconductor processing laboratory, including commissioning deposition systems and integrating in-situ characterization and metrology tools, enabling scientists to pursue materials discovery.
Equipment Qualification & Troubleshooting: Establish equipment specifications, acceptance criteria, and qualification protocols for new tools; diagnose and resolve complex hardware, vacuum, and process-equipment failures.
Vendor & Procurement Engagement: Contribute to vendor communication and tool selection, providing technical requirements to vendors and supporting bid evaluation and technical negotiation, in coordination with the procurement team.
Documentation & Data: Create internal and external documentation, equipment SOPs, strategies, and technical reports, and establish standardized equipment data pipelines to feed into AI training infrastructure.
Equipment Reliability & Uptime: Own day-to-day equipment health and prioritize tool availability by proactively monitoring performance, troubleshooting hardware and process issues, performing root-cause analysis, and working directly with vendors to resolve failures quickly and prevent recurrence.
You Will Thrive in This Role If You Have
BS, MS, or PhD in Engineering (Mechanical, Chemical, Electrical), Materials Science, or a related field.
Extensive hands-on experience with vacuum systems in a semiconductor, nanofabrication, or advanced materials setting.
Deep expertise in high-vacuum system operation and the underlying mechanisms of deposition hardware, including plasma sources, gas delivery, and thermal management.
Experience integrating characterization and metrology capabilities directly into process equipment (e.g., in-situ metrology, environmental chambers).
Startup-ready mindset: able to operate effectively in a fast-paced, ambiguous environment while implementing industry-standard best practices.
Mechanics
Type: Full-time
Location: On-site in Menlo Park, CA. This role cannot be performed remotely.
Schedule: Standard weekday schedule.
Compensation: $200K to $275K, plus equity, commensurate with experience.
Work authorization: Must be authorized to work in the U.S.; visa sponsorship available for exceptional candidates.