53 parallel-computing-numerical-methods "Institute of Computer Science" Postdoctoral positions at Argonne
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processing approaches and dry head-end separations methods; evaluating process performance; and contributing to technical reports, publications, and sponsor deliverables. The successful candidate will work
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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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. Working with staff and extensive partner members (including LANL, LLNL, SNL, and numerous national and international academic and other institutions) The Postdoc will have long term career growth and future
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partners. Responsibilities will include designing and conducting experiments, developing slurry-based processing methods, building and operating materials recovery systems, analyzing material transport and
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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research in the field of metallization and decarbonized metal production, using methods such as aqueous electrolysis, non-aqueous electrolysis, and molten salt electrolysis. The candidate will conduct
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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on understanding novel and emergent behavior in nanoscale magnetic heterostructures, particularly in confined 2D van der Waals magnets and related devices. The goal of the program is to study and control magnetic
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with staff and extensive partner members (including LANL, LLNL, SNL, and numerous national and international academic and other institutions) The Postdoc will have long term career growth and future
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molten-flux growth (metals, chalcogenides, halides, and hydroxides), Bridgman crystal growth, chemical vapor transport, and related methods. 2. Hands-on experience with materials characterization