Postdoc: AI-Driven Spectromicroscopy Software

Lawrence Berkeley National Laboratory; San Francisco (CA); On-site; USD 99,000 - 111,000; Full time

Job summary

Lawrence Berkeley National Laboratory seeks a Scientific Software Postdoc to advance autonomous spectromicroscopy at ALS beamlines. You will develop ML methods for real-time analysis and build an agentic AI component to direct instrument control, integrating it with beamline software for robust, real-time decision making.

You will collaborate across disciplines, publish results, and contribute to open-source software, aiming to enable autonomous, intent-driven experimentation at scale.

Qualifications

• PhD degree in the Physical Sciences, Material Science, Applied Mathematics, Electrical Engineering, Computer Science, or related discipline.
• Experience and a strong interest in scientific software development or research software engineering.
• Knowledge of machine learning principles and practices.
• Familiarity with agentic AI systems and concepts.
• Ability to work collaboratively with a diverse team of scientists and engineers.
• Demonstrated record of scientific excellence through publications, talks, or software deliverables.
• Commitment to collaborative software development practices: version control and code review, unit testing, and CI.

Responsibilities

• Investigate and validate machine learning or computational methods for real-time analysis of X-ray spectromicroscopy data at an ALS beamline.
• Create/extend an agentic component using modern AI techniques to interpret multimodal scientific input to formulate instrument commands.
• Integrate this agentic component with real-time analysis results and beamline control into a unified system.
• Participate in experimental planning, commissioning, troubleshooting, and data-quality assessment.
• Apply human-in-the-loop, validation, and fail-safe approaches when developing AI-enabled experimental control workflows.
• Collaborate with scientists, engineers, and external collaborators.
• Contribute to open source scientific software and release project outputs where appropriate.
• Present findings at scientific meetings and in peer-reviewed journals.

Skills

Machine learning

Agentic AI

Scientific software

Python

CI/CD

Communication

Education

PhD in Physical Sciences

Tools

Python ecosystem

Job description

Lawrence Berkeley National Laboratory seeks a Scientific Software Postdoc to advance autonomous spectromicroscopy at ALS beamlines. You will develop ML methods for real-time analysis and build an agentic AI component to direct instrument control, integrating it with beamline software for robust, real-time decision making.

You will collaborate across disciplines, publish results, and contribute to open-source software, aiming to enable autonomous, intent-driven experimentation at scale.