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Materials and Membrane Manufacturing group combines fundamental materials synthesis insight with realistic scaling and application-driven design to create disruptive new materials advances. In addition
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environment that brings together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for
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, morphology, and device-relevant properties Design active learning, Bayesian optimization, uncertainty-aware modeling, and other adaptive experimental design workflows to guide experiments and
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. The candidate will conduct research related to a wide range of topic areas including the analysis of energy and power systems, electricity market design and operation, power flow modeling, energy
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is extended yearly. Position Requirements A recent PhD (within 5 years) in computational chemistry, chemistry, materials science, physics, computational science, computer science, engineering, or a
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with computational scientists in other divisions, including Mathematics and Computer Science (MCS) and the Argonne Leadership Computing Facility (ALCF). The group has significant involvement in three
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research group and with scientists from a variety of scientific backgrounds, such as microbiology, chemistry, x-ray physics, hydrology, geochemistry, soil science, and computer modeling. In this role you
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-duty vehicles, hybrid, battery electric and fuel cell powertrain design, development of supervisory control logic, validation of vehicle models against test data etc. The projects and interests of this
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The Argonne Accelerator Institute (AAI) at Argonne National Laboratory is seeking a postdoctoral researcher for a multi-year appointment to contribute to the conceptual design of a compact, wakefield
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Argonne’s High Energy Physics Division, the successful candidate will contribute to the design, fabrication, and characterization of superconducting devices based on microstrip-coupled TES technology