305 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions at University of Oslo
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to apply: https://www.jobbnorge.no/en/available-jobs/job/291009/phd-research-fellow-in-criminology Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/291009/phd-research-fellow-in-cr
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integration of welfare technologies in the care systems for elderly people. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/292367/phd-research-fellow-in-human-robot
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environment for the training and development of PhD candidates and postdoctoral fellows, including individually tailored career development plans with formal supervision and project-based learning. Secondments
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biology, advanced imaging, and 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
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Africa and Europe. The network will consist of 15 PhDs, that together will work and learn as an international cohort and collaborate across projects to bring together insights anchored in different sectors
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an international and interactive environment. Candidates must have extensive experience with: Programming (including MATLAB) and computational modelling Machine Learning (ML) methodology applied for complex data
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of Psychology at the University of Oslo (UiO). Learn more about working at PROMENTA here . About the NeuroPathways Convergence Environment and the PhD project Convergence Environments are interdisciplinary
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: https://www.mn.uio.no/math/english/research/groups/several-complex-variables/index.html https://www.mn.uio.no/math/english/research/groups/operator-algebras/index.html The Faculty of Mathematics and
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of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
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Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies