47 assistant-professor-computer-science-and-data-"St"-"St" Fellowship positions at University of Oslo
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and the Master's programme in clinical nutrition. The Institute has more than 300 employees and is located in Domus Medica. Questions about the position Ragnhild Eskeland Associate Professor +4722851457
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Data Science. Questions about the position Aksel Ørbeck Seniorrådgiver HR +4799625749 personalgruppen@sv.uio.no Robert Huseby Professor +4722855189 roberthu@stv.uio.no Apply for this job Deadline 1st
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students, researchers, technical- and administrative staff. The Department has around 200 employees. Questions about the position For further information please contact: Ivar Midtkandal Professor +47
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must hold a degree equivalent to a Norwegian doctoral degree in computer science, statistics, mathematics, data science, or related fields. Doctoral dissertation must be submitted for evaluation by
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requirements: Applicants must hold a degree equivalent to a Norwegian doctoral degree in epidemiology, biostatistics, computational biology, or a related field, with a strong quantitative background. Doctoral
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computer science, statistics, mathematics, data science, or related fields. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public
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training leading to the successful completion of a PhD degree. The fellowship requires admission to the PhD program at the Faculty of Mathematics and Natural Sciences. The application to the PhD program must
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with respect to academic credentials. Qualification requirements: Master’s degree or equivalent in Artificial Intelligence Computer Science Foreign completed degree (M.Sc.-level) corresponding to a
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. Qualification requirements: Master’s degree or equivalent in physics, process technology, or computational geosciences Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in
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combining the mathematical and computational cultures, and the methodologies of statistics, logic and machine learning in unique ways, Integreat's machine learning will solve fundamental problems in science