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- University of Oslo
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- UiT The Arctic University of Norway
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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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systems for use in breaking waves, both in the field and in the lab Contribute to analysis of images, and development of the open-source analysis software PyOPIA (https://github.com/SINTEF/pyopia
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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 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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and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland Norway’s research group for User Perception and Engagement in XR
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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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the organizational structure of the belligerents. WOW will theorize, identify, classify, and code the characteristics of state military organizations and non-state armed groups and collect data relating
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Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field observations—including
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factories and warehouses with autonomous components. It addresses a fundamental challenge in industrial digitalization: the lack of formal, machine-interpretable representations that integrate structural
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. The project is supervised by Associate Professor Ulysse Côté-Allard at the Department of Technology Systems, University of Oslo, whose research focuses on the development of machine learning algorithms