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or soon-to-be completed (typically within the last 0-5 years) in Materials Science, Chemical/Mechanical Engineering, Chemistry, Condensed Matter Physics, or a closely related field. Demonstrated experience
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-house codes and making use of high-performance computing (HPC) tools. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical, aerospace
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catalytic mechanisms and reaction outcomes • Perform detailed in situ / operando studies of catalysts using Infrared and X-ray Absorption Spectroscopies, as well as other advanced spectroscopic techniques
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phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in multiphase systems Use modeling tools such as computational fluid
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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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automated experimental systems to measure electrode performance and durability over extended operation. Investigate electrode material performance, aging, and degradation mechanisms for bioprocessing
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mechanisms through reaction kinetics analysis and other physical organic and inorganic techniques Perform detailed in situ / operando studies of catalysts using X-ray Absorption and Emission Spectroscopies
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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The X-ray Imaging Group (IMG) of the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in computational science and image processing to develop innovative methods