Full-Time
Research Scientist
Materials Characterization
Posted on 10/4/2025
Periodic Labs
51-200 employees
AI-driven materials discovery and design
No salary listed
Menlo Park, CA, USA
In Person
 Data & Analytics (1) |
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- PhD in Physics, Materials Science, or related field, with 5+ years of hands-on experience in the field
- Deep, demonstrated expertise in physical property characterization including electronic and magnetic measurements
- Strong background in cryogenic measurements and low-noise techniques (lock-in methods, shielding/grounding, precision instrumentation).
- Strong track record of performing 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.
- Excellent scientific writing, collaboration across disciplines, and strong ownership of experiment quality.
- Physical Property Measurements: Develop and perform high-fidelity thermodynamic, transport, and spectroscopic measurements of materials
- High-throughput Screening: Develop rapid property measurement schemes to scale up the material characterization process
- Analysis: In collaboration with our AI team, implement automated data analysis and reasoning pipelines for screened materials
- Automation: In collaboration with our engineering team, develop autonomous systems for property characterization leveraging robotics
- Experience with automation of physical property measurements
- Previous experience with computational prediction and experimental characterization design loop
- Experience with lab buildout and process safety
- Experience with handling data at scale
Periodic Labs uses AI to model, predict, analyze, and design new materials. Its platform studies material properties and high-throughput data to propose viable compositions, structures, and processing methods that meet performance targets. By training models on large scientific datasets and running simulations, the company speeds up discovery and lowers costs compared with traditional lab work, drawing on founders’ experience from OpenAI and DeepMind. The goal is to accelerate the discovery of materials for clean energy, better semiconductors, and resilient manufacturing, differentiating itself through deep AI expertise applied specifically to materials science and potential collaboration with major AI groups.
Company Size
51-200
Company Stage
Seed
Total Funding
$300M
Headquarters
San Francisco, California
Founded
2025
Simplify's Take
What believers are saying
- Raised $300M seed in September 2025 from a16z, Nvidia, Bezos, and others valuing at $1.5B.
- Secured partnerships with semiconductor makers improving chip heat dissipation since October 2025.
- In talks for hundreds of millions at $7B valuation as of early 2026.
What critics are saying
- DeepMind's GNoME dataset from Cubuk's 2023 project blocks replication in 6-12 months.
- Matlantis launches superior simulations in Q1 2026, undercutting chip partnerships.
- Commerce export controls halt Nvidia AI chip supply in March 2026.
What makes Periodic Labs unique
- Founders Liam Fedus and Ekin Dogus Cubuk combine OpenAI and DeepMind expertise in AI materials science.
- Builds autonomous robotic labs running thousands of experiments daily with gigabytes of unique data.
- Deploys AI agents with physical labs for semiconductors, space, defense, and nuclear fusion applications.
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Benefits
Professional Development Budget
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -8%2 year growth
↓ -8%Periodic Labs has raised from a tech industry who's who, including Andreessen Horowitz, Nvidia, Elad Gil, Jeff Dean, Eric Schmidt, and Jeff Bezos.
Venture firm Andreessen Horowitz has agreed to lead a $200 million investment in Periodic Labs, a new startup building artificial intelligence for material science, according to people familiar with the matter.