Skip to content
Periodic Labs

Research Scientist, Materials Characterization

Menlo Park, CAOnsite · United States
FullTime · Science
POSTED 9 JUL
Apply Ask
Role
123 days opentrue age
Posted 9 Jul
Pay
$275k–$300kno pay posted
$200k$425k
Market p25–p75
$200k–$300k
Periodic Labs p25–p75
$275k–$300kn=9
H-1B median · ML / AI
$425k
SF Bay Area · n=461 · 365d to 6 Nov
CompanyPeriodic Labs →
32open roles
Opened · 30d
+0
Closed · 30d
−0
3d of snapshots · 30d window
Market
3,251open · ML / AI
Opened · 7d
+2277% of open
All ml / ai
6,608open
All tracked boards · live 10 Nov · n=3,251
Visa
7H-1B LCAs · FY26
Median wage
$375k
LCAs FY26 · n=7 · to 2026-05-26
Python

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

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.

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

Mechanics

Minimum education: Bachelor’s degree or similar experience

Employment type: Full-time, 12-month term

Source · Periodic LabsFirst seen 2 NovOriginal ↗