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interdisciplinary teams across DOE National Laboratories. Publish impactful research in peer-reviewed journals and support related projects within the team. Enhance professional skills, including communication
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physics knowledge into DL model design and training, these models outperform traditional methods even without labeled training data (https://www.nature.com/articles/s41524-022-00803-w ). Application spaces
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geometry manipulation with computer-aided design software. Experience with coupling CFD and FEA codes. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and
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of time-resolved microscopy / spectroscopy experimental platforms for quantum material research. The ability to lead interdisciplinary research projects in a highly collaborative environment. Experience
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research projects, data analysis, physics interpretations, and reporting of the results. A strong background in the field of Experimental Nuclear Physics. Ability to model Argonne’s core values of impact
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, including object stores, memory-X and filesystems, to research and develop strategies to evaluate, profile and optimize AI applications at scale. Another key objective is to help us with design of future