Research Associate, Thin Films

About the Role

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.

What You’ll Do

• 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.

You Will Thrive in This Role If You Have

• 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.

Especially Strong Candidates May Also Have

• 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

• PhD or similar experience
• Location: Menlo Park, CA

Compensation

$180,000-$225,000 + equity

Visa sponsorship: Yes, we sponsor visas and will do everything we can do assist in this process.