33 machine-learning-"https:" "https:" "https:" Fellowship positions at University of Oslo
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theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project
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project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD fellow will be part of a growing
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, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts. This position is part of the DRIVE project, funded by the Research Council of Norway
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of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations
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convergence of high-performance computing (HPC) and AI, which is a subject that sees an increasing importance due to the widespread use of AI and in particular machine learning (ML). As today’s mainstream AI/ML
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on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co
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of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project addresses the development of trustworthy statistical and machine learning methods for anomaly
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of Oslo’s Department of Informatics (IFI) and is hosted by the Network and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland
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or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants
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is part of the ERC-funded project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD