201 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in Norway
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thermal imaging data, and potential clinical and signal data, to create algorithms capable of recognizing key clinical activities and interventions. Building on recent advances in computer vision and
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one in Tromsø (UiT The Arctic University of Norway). Machine learning is the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of
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the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language technology, ethics and machine learning, in new and unique ways. The focus of Integreat is to develop
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PhD Research Fellow in applied and computational mathematics Apply for this job See advertisement UiB - Knowledge that shapes society Through robust and close interaction with the world around us
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technologies, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with our current PhD students
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properties of the Higgs boson. The group focuses on final states containing several tau-leptons. The analysis activity is now extended to include generic anomaly searches using Machine Learning. Furthermore
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anomaly searches using Machine Learning. Furthermore, the group takes part in ATLAS upgrade, with participation in the ITk-Pixels project, with responsibilities concerning testing and delivery of pixel
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before application deadline. Strong programming skills and experience with AI, computer vision, image analysis and deep learning are advantages. Knowledge of hematology, cytology and pathology is a plus
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and science, as well as PhD education in computer technology. The Mohns Center for Innovation and Regional Development researches innovation and offers master's education in innovation and
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning