About the RoleJoin 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.
What You'll Do- 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
You Will Thrive in This Role If You Have- 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
Especially Strong Candidates May Also Have- 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
MechanicsMinimum education: Bachelor's degree or an equivalent combination of education and training or 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: The annual base compensation range for this role is $225,000-325,000, commensurate with experience
Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process with our legal support.
