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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep-learning
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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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UiO/Anders Lien 9th February 2026 Languages English English English Join a supportive team at the University of Oslo as a PhD Research Fellow in Deep Learning for medical imaging! PhD Research
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University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research Fellow in Deep learning for subsurface imaging Apply for this job See advertisement About the position Position
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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cameras, heart rate monitors, and dedicated activity trackers for data collection and employ relevant machine learning methods for data analysis and sensor fusion. The PhD Research Fellow will collaborate
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dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in
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implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong