637 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" positions in Norway
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leaders and teachers. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/297979/potdoctoral-research-fellow-in-childrens-learning-and-development Where to apply Website
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and research, in and outside academia. The position will specifically focus on Reinforcement Learning for Resource-Constrained Project Scheduling Problem (RCPSP). The Ph.D. candidate will be a member of
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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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, methods and practices are put to work in disciplinary contexts outside the art field (i.e. the environmental humanities, media studies, anthropology, STS, cultural geography). The degree must normally
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interfaculty centre with 10 permanent academic staff, 2 postdoctoral fellows, and 7 PhD candidates. Staff and PhD candidates conduct research, teach, and engage in outreach in the field theory of science
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and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with AI / probabilistic AI / Machine Learning / Reinforcement Learning Experience with numerical
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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
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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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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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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