272 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" research jobs at University of Oslo in Norway
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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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machine learning techniques to develop emulators for the theoretical predictions of various observables as function of cosmological parameters. The candidate will develop and use skills in topics such as
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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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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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the upper segment of their class with respect to academic credentials. Required qualifications: Master’s degree or equivalent in mathematics, physics, control, cybernetics, computer engineering, automation
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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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: 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