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: Applicants must hold a master's degree or equivalent education in applied physics or mathematics or a relevant engineering subject (e.g. mechanical, aerospace, chemical, or process safety). Master students can
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personal qualities: Applicants must hold a master's degree or equivalent education in reservoir physics, applied mathematics, chemical engineering, geoscience, applied petroleum technology, or a related
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computer science or statistics A solid background in mathematics, linear algebra and statistics. Documented experience with Bayesian spatiotemporal modelling, including experience with the INLA framework
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. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in Informatics, Physics or Mathematics, or must have submitted his/her master's thesis for assessment prior
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PhD Research Fellow in Experimental Fluid Mechanics: Tunable hairy surfaces for droplet flow control
of the fellowship is research training leading to the successful completion of a PhD degree. The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application
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, methods and applications. The areas represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and
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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
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of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics. The Department has more than 1800 students on bachelor
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with respect to academic credentials. Qualification requirements: Master’s degree or equivalent in computer science or statistics A solid background in mathematics, linear algebra and statistics
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represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology