Postdoctoral Researcher – Machine Learning for Materials Science

Lawrence Berkeley National Laboratory • Berkeley, CA

1d • $99,192 - $110,808 • Onsite

About The Position

Lawrence Berkeley National Laboratory is hiring a Postdoctoral Researcher – Machine Learning for Materials Science within the Molecular Foundry division. Molecular Foundry is a Department of Energy-funded nanoscience research user facility that provides access to cutting-edge expertise and instrumentation in a collaborative, multidisciplinary environment to scientists from around the world. Through a peer-reviewed applications process, scientists gain access to our facilities and become users of our scientific tools and expertise.
The Postdoctoral Researcher will work at the Molecular Foundry in collaboration with researchers from Argonne National Lab and Oak Ridge National Lab on a collaborative Department of Energy funded project “AlphaFold for Microelectronics”. The role will be to develop data infrastructure to capture and curate both experimental and simulation data and collaboratively build machine learning models to predict behavior of novel materials for memristor applications. This is an opportunity to contribute to a vibrant research community dedicated to doing excellent science in a supportive and inclusive environment.

Requirements

• Ph.D. in Physics, Chemistry, Material Science, Computer Science or a closely related field.
• Demonstrated knowledge of Python or another major programming language for data analysis and familiarity with machine learning approaches for data analysis.
• Knowledge of Machine Learning methods for materials science applications.
• Strong organizational skills including the ability to prioritize work, meet deadlines, and contribute to the planning of a scientific research program.
• Excellent oral and written communication skills including the ability to organize technical/scientific information, publish in top journals, and present at conferences.
• Strong teamwork and interpersonal skills including the ability to collaborate with a diverse interdisciplinary research team.

Responsibilities

• Collaborate with scientists in developing workflows to capture data and metadata for both experiments and simulations and store them in the Crucible data platform.
• Collaborate with experimental and computational researchers to define appropriate metadata, data-quality requirements, and analysis-ready data structures.
• Develop machine learning models that integrate multimodal experimental and simulation data.
• Contribute to the development of Crucible Data Platform using software best practices.
• Present research results at national conferences and author publications.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree