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qualitative, quantitative, and/or mixed-methods research designs Demonstrated ability to collaborate effectively with educators and community partners Experience with externally funded research or proposal
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quantum many-body methods, such as GW combined with dynamical mean-field theory (DMFT), for strongly correlated electron systems. Candidates should also have a strong research record in correlated quantum
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devices. The successful computational candidate must hold a Ph.D. in Physics or a closely related field and demonstrate expertise in developing quantum many-body methods, such as GW combined with dynamical
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experience (front-/back-end, metrology/inspection, equipment maintenance, yield-improvement projects). Digital twin, IIoT, MLOps, real-time data streaming, edge computing. Causal/XAI, Bayesian methods
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control to improve part quality, reduce defects, and tailor anisotropic performance. Integration of advanced post-processing methods to improve the structural integrity, performance, and reliability
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method development & optimization: Proven ability to develop, optimize, and validate LC-MS/MS methods for complex sample types. Expertise in extracting proteins, metabolites, and lipids and performing nano