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related to battery materials, correlated electron calculations, including via DFT+U, supercells, dynamical mean field theory or experience in defect and/or alloy calculations, machine learning, and other
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pathology on computational, molecular, cellular, preclinical and translational levels. A spectrum of scientific methods includes state-of-the-art multi-omics approaches, machine learning and implementation
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, computer scientists, and policy experts. The postdocs will work with Prof. Daniel Loveless on various areas of research, including radiation and reliability effects in emerging semiconductor technologies
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