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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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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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represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology
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and society. Integreat draws on the research strengths of researchers and students from the departments of Mathematics, Informatics, Philosophy, and the Oslo Centre for Biostatistics and Epidemiology
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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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is a new initiative that organises the local bioinformatics community and drives bioinformatics innovation by integrating computational and biological sciences to address complex life 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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computational and biological sciences to address complex life science challenges. It fosters collaborations and develops advanced computational tools through a hub for multi-omics and systems biology. Project
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The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in