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on the U.S. energy sector. Our research seeks to inform public and private decision-making on issues such as electricity system planning, energy resources and delivery, new large loads, reliability
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theoretical chemistry tools to investigate ultrafast and quasi-equilibrium phenomenon for large, and complex interfacial systems. A primary goal will be bridging the time scale and length scale gap for non
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new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. This role involves research and
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python. Experience with machine-learning, such as training large language models. Required Application Materials: CV Cover Letter (1 page) Publication List Additional information: Application date
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reasoning over large scientific data sets. Developing theories for materials synthesis and degradation. Preparing presentations and reports. Writing peer-reviewed journal articles. We are looking for: PhD in
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of Perlmutter and connect directly to DOE experimental and observational facilities so research teams can stream and analyze data in near real time. You will collaborate with NERSC staff, domain scientists, and