The Data Science and Learning Division (DSL) of the Computing, Environment and Life Sciences Directorate (CELS) and the Materials Science Division (MSD) of the Physical Sciences and Engineering Directorate (PSE) at Argonne National Laboratory is seeking applicants for a Postdoctoral Appointee who will conduct cutting-edge research in AI for Materials Science Discovery, with a focus on critical materials complexation and conversion, and energy storage and conversion. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using AI, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI/ML model development to design and discover redox-active materials with tunable properties (structure, charge state, etc.) Discovery of novel materials for energy storage and conversion and their characterization with advanced computational chemistry tools, including molecular dynamics, density functional theory and Grand Canonical Monte Carlo simulations.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees