Autonomous Materials AI Scientist (Postdoc)

Lawrence Berkeley National Laboratory; San Francisco (CA); On-site; USD 92,000 - 103,000; Full time

Benefits offered by this job

PTO and holidays

Postdoctoral Paid Family Leave

Berkeley Lab Postdoc Association

Collaborative culture

Job summary

The Energy Technologies and Systems Division at Lawrence Berkeley National Laboratory invites applications for a Postdoctoral Scholar to join the Jain (HackingMaterials) group and advance autonomous science across two major projects.

You will build autonomous simulation agents, scale MLIP/DFT workflows on HPC, validate predictions against experiments, and contribute to catalysis databases and AI-driven discovery platforms.

Qualifications

• PhD in a related field from an accredited institution.
• Experience with MLIPs and DFT workflows (e.g., VASP, atomate2) and HPC scaling.
• Broad knowledge of solid-state materials science and independent work in large teams.

Responsibilities

• Develop autonomous simulation agents predicting ion transport and related properties.
• Scale MLIP/MD/DFT workflows on HPC for hundreds of compositions.
• Validate predictions against experimental campaigns and integrate into live campaigns.
• Contribute to a catalysis database and AI-driven catalyst design.

Skills

MLIPs

DFT workflows

HPC scaling

Solid-state materials science

Education

PhD in Materials Science, Chemistry, Physics or CS

Tools

VASP

atomate2

Job description

The Energy Technologies and Systems Division at Lawrence Berkeley National Laboratory invites applications for a Postdoctoral Scholar to join the Jain (HackingMaterials) group and advance autonomous science across two major projects.

You will build autonomous simulation agents, scale MLIP/DFT workflows on HPC, validate predictions against experiments, and contribute to catalysis databases and AI-driven discovery platforms.