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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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. 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
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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
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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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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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engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written communication skills In-depth knowledge
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browser and try again. UiO/Anders Lien 25th June 2026 Languages English English English PhD Research Fellow in Professional/Workplace Learning with Emerging Epistemic Technologies Apply for this job See
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expertise in discrete choice modelling, statistical modeling, traffic simulation, machine learning, and optimization techniques. • Strong expertise in discrete choice modelling, statistical modelling, and
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.” About the Opportunity The Khoury College of Computer Sciences seeks a Distinguished Research Fellow to establish and lead an independent research program. The Distinguished Research Fellow will be