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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment spanning physics, neuroscience and computational science
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machine learning and AI techniques to improve prediction of contaminant transport, sediment dynamics, and ecosystem exposure in complex fjord environments. The research will benefit from extensive
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exam before 15.06.2026. It is a condition of employment that the master's degree has been awarded. Background in optimization is required. Experience in machine learning is an advantage. Familiarity with
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, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies (mAbs) used in autoimmune, inflammatory, and neurological diseases. Using
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UiO/Anders Lien 9th February 2026 Languages English English English Join a vibrant team at the University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research
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. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning models that forecast
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Learning for Medical Imaging and Multi-Modal Data in Cancer Research Apply for this job See advertisement About the position Position as PhD Research Fellow in Deep Learning available at the Department
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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep learning for imaging of marine
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machine learning. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities