242 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" research jobs at University of Oslo
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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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of illness to the ways medical knowledge, technologies, and policies shape societies. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/292473/research-assistant-position-20
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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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environment spanning physics, developmental biology, advanced imaging, and machine learning. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and Natural
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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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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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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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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
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the areas of stochastic analysis and computational methods towards machine learning with focus on risk-sensitive decision making and control. Techniques may include forward, backward stochastic differential