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-optimization of industrial end-use systems and energy supply systems. Build reproducible computational workflows for data processing, model development, calibration, validation, and scenario analysis. Develop
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. The candidate will work closely with computational modeling collaborators to validate reactor designs and optimize operating parameters. The candidate will be expected to contribute to report preparation
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications
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The Chemical Sciences and Engineering Division seeks a Postdoctoral Appointee to conduct research focused on the development of high-energy, long-cycle-life lithium–sulfur batteries employing both
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collaboration and innovation. Position Requirements This level of knowledge is typically achieved through a formal education in Statistics, Machine Learning, Computer Science, Logistics/Supply Chain, or a related
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have a strong background in fundamental electrochemistry, with preferable hands-on expertise in computational materials science. The applicant should be well versed in code development, application of AI
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the past 0–5 years) in Atmospheric Science or a related field Demonstrated expertise in one or more of the following areas: convective storms, precipitation processes, severe winds, land–atmosphere
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Perform advanced characterization using synchrotron-based X-ray techniques to investigate material behavior and interfacial chemistry during synthesis and battery operation Develop mechanistic understanding
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conditions to fabricate membrane components with desired physics and ionic transport properties. As part of the Materials Engineering Research Facilities (MERF), the Nanocomposite Materials and Membrane
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field Strong foundation in electrochemistry, electrochemical engineering, and chemical processing Demonstrated experience in mathematical modeling of electrochemical systems; knowledge of solid mechanics