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physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in
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Requirements: Preferably PhD in computer science or related field. Expertise in computer programming Knowledge in machine learning Proven research ability as evidenced through a portfolio of publications and/or
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learning to model solid-state materials while collaborating with experimentalists. Qualifications • Ph.D. in Computational Physics/Materials Science, or related field (completed by start date
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position The USN School of Business has three vacancies for 100 % positions as PhD Research Fellows in the PhD programme in Management from 01.01.2026. The positions will be affiliated with one
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The newly established Program for Memory Longevity (PML), led by Attila Losonczy, MD, PhD, in the O’Donnell Brain Institute (OBI) and the Department of Neuroscience at the University of Texas
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. The hired candidate will be admitted to the PhD program in Science and Technology. The education includes relevant courses amounting to about six months of study, a dissertation based on independent
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system engineering, Physics or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning). The Master’s thesis must be included in the application. Ideal
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that the candidate will acquire from the PhD project, including positions that entail software development, engineering or consulting for the energy or process industry, and academia. The career promoting work will
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market for personnel with the knowledge and skills that the candidate will acquire from the PhD project, including positions that entail software development, engineering or consulting for the energy or
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search using vacancy reference B02-09130. About you You will have a PhD in Computational Biology, Applied Mathematics, Statistics, Biostatistics, Epidemiology, Bioinformatics, Computer