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boson decays, searches for supersymmetry and other new phenomena, and measurements of rare standard model processes. We vigorously pursue the use of machine learning techniques for data analysis
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the candidate with access to world-class computational and AI resources as well as a vibrant physics community and connections with Fermilab and Argonne National Laboratory. Qualified candidates must have a PhD
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pursue the use of machine learning techniques for data analysis. Candidates must have a Ph.D. and research experience in experimental high energy physics. The successful candidate is expected to carry out
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involved in SpinQuest at Fermilab and the MUSE experiment at PSI. Our hardware program includes the ePIC Barrel Imaging Calorimeter, and instrumentation R&D such as a polarized lithium-ion source for EIC