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The Nuclear Science and Engineering (NSE) division advances the design and operation of nuclear energy systems and applies nuclear energy-related expertise to current and emerging programs
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are critical tools for the design and analysis of interfacial materials and will play a vital role in this research. In this role, the postdoctoral fellow is expected to work with domain experts and experimental
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The Cosmological Physics and Advanced Computing (CPAC) group at Argonne invites applicants for a postdoctoral associate to conduct research on topics related to theory and modeling of large-scale
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learning to interpret experimental x-ray and electron characterization data. The postdoctoral researcher will work within the group of Dr Maria Chan (https://www.anl.gov/profile/maria-k-chan) on developing
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Source (APS). You will also perform pre- and post-irradiation examinations using FIB, SEM, and TEM. Furthermore, you will compare and validate predictions of nuclear material performance characteristics
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behavior, materials, neutronics, thermal-hydraulics, and structural mechanics. The candidate will assist in investigation of the performance of nuclear fission reactors and fuel cycle facilities and
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of Energy projects. Position Requirements Ph.D. in Electrical Engineering, Computer Science, Operations Research, or a related field. Demonstrated expertise in control and optimization techniques
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on correlated layered materials. The work will be in close collaboration with other theoretical and experimental groups and will entail working out theory of correlated phases in topological materials, proposing
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primarily work with Prof. G. Galli, Prof. F.Gygi, Dr. M. Govoni, Dr. Y. Wenzhe and with a team of 10+ PhDs/postdocs contributing to the development of codes currently supported by MICCoM (http://miccom
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candidate will have the opportunity to develop, use, and deploy state-of-the-art tools on the largest supercomputers used for scientific computing. The work is part of a larger collaboration between Argonne