Postdoctoral Scholar

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

Benefits offered by this job

Health benefits

Retirement plan

PTO 24 days per year

Postdoc Paid Family Leave

Postdoc Association

Job summary

Lawrence Berkeley National Laboratory's Energy Technologies and Systems Division seeks a Postdoctoral Scholar to join the Jain (HackingMaterials) group for autonomous science projects, building simulation agents to predict materials properties and enabling live experimental campaigns at Berkeley Lab.

The role starts November 1, 2026, is a full-time, two-year appointment with potential renewal, and involves collaboration across multi-institution teams to advance AI-driven discovery in catalysis

Qualifications

• Ph.D. in a relevant field (Materials Science, Chemistry, Physics, CS) is required.
• Demonstrated strong Python programming skills.

Responsibilities

• Develop autonomous simulation agents to predict Li-ion conductivity and related properties.
• Build and scale MLIP/MD/DFT workflows on HPC infrastructure.
• Validate predictions against experimental campaigns and integrate into live campaigns.

Skills

Python programming

HPC experience

Materials science knowledge

Education

Ph.D. in Materials Science, Chemistry, Physics, Computer Science, or related field

Tools

VASP

atomate2

Job description

The Energy Technologies and Systems Division at Lawrence Berkeley National Laboratory is seeking a Postdoctoral Scholar to join the Jain (HackingMaterials) group within the Applied Energy Materials group at the frontier of autonomous science across two projects. The primary assignment for the first 9 months is A-WILD (AI-driven Workflows for Intelligent Lab Discovery), a DOE Genesis Mission project building a self-improving, closed-loop discovery engine that couples AI hypothesis generation with the A-Lab, Berkeley Lab's fully autonomous laboratory for inorganic materials synthesis and characterization. You will build simulation agents that predict materials properties (such as Li-ion conductivity in solid electrolytes) autonomously and at scale, validate them against thousands of real A-Lab experiments, and connect them into live experimental campaigns so that AI checks every candidate before it reaches the robot deployed on the Genesis American Science Cloud with the Materials Project as computational backbone.

You will then transition to PANDORA, an ARPA-E-funded closed-loop AI platform for catalyst discovery targeting CO2 conversion to fuels and chemicals, where the group leads the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a computational scientist eager to demonstrate, quantitatively, that AI can drive scientific discovery faster than pure human iteration.

This position has an anticipated start date of November 1, 2026.

We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!

Why join Berkeley Lab?

Benefits

We invest in our postdoctoral scholars by offering benefits and resources designed to support your well-being, professional growth, and life outside of work:

• Comprehensive health benefits , including medical, dental, and vision coverage.
• Retirement savings through the UC Defined Contribution Safe Harbor Plan, with additional voluntary UC retirement savings options available.
• 24 days of Personal Time Off (PTO) per fiscal year, plus sick leave and paid holidays .
• Eight weeks of Postdoctoral Paid Family Leave for qualifying family and parental needs.
• Opportunities to connect, network, and grow through the Berkeley Lab Postdoc Association , including social events, professional development, and scientific exchange.
• A collaborative and inclusive culture where you can grow your research career and belong.

You Will

• Develop autonomous simulation agents that predict Li-ion conductivity and related properties for candidate compositions, returning a value, an error estimate, and a full record of how it was computed.
• Build and scale MLIP/MD/DFT workflows (e.g., atomate2, MACE/CHGNet/UMA-class potentials) to hundreds of compositions on HPC.
• Validate predictions against A-Lab experimental campaigns and integrate simulation agents into live campaigns through AlabOS APIS.
• Compute first-principles active-site descriptors for $ ext{CO}_2$ conversion catalysts (vacancy formation energies, adsorption energies, metal-support interactions) and correlate them against measured kinetic parameters.
• Contribute to multi-agent hypothesis generation and validation architectures and to a curated catalysis database supporting AI-driven catalyst design.
• Release data, workflows, and benchmarks via the Materials Project and Genesis AmSC; publish in peer-reviewed journals and present at conferences.

We Are Looking For

• Ph.D. in Materials Science, Chemistry, Physics, Computer Science, or a related field.
• Demonstrable strong Python programming (programming portfolio required).
• Experience with MLIPs and DFT workflows (e.g., VASP, atomate2).
• Experience running and scaling simulations on HPC.
• Broad knowledge of solid-state materials science.
• Ability to work independently within a large multi-institutional team.

Desired Skills/knowledge

• Experience with agentic frameworks.

For Consideration, Please Apply The Following Application Materials

• Cover Letter - Describe your interest in this position and the relevance of your background.
• Curriculum Vitae (CV) or Resume.

Additional Information

• Application date: Applications will be accepted until the job posting is removed.
• Appointment type: This is a full-time, 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
• Salary range: The monthly salary range for this position is $8,266 / mo - $9,234 / mo and is expected to start at $8,266 / mo or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral and/or related research experience.
• Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work modality: This position will be performed on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
• Union Represented: This position is represented by a union for collective bargaining purposes.

Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.

Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer. For additional information, click here .