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computer science, statistics, mathematics, data science, or related fields. Strong background in statistics and linear algebra. Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in
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degree or currently working on finalizing master thesis in computer science, statistics, mathematics, data science, or related fields. Strong background in statistics and linear algebra. Foreign completed
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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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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