362 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" Fellowship positions in Norway
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which also include health care services. More practical information about working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that the application will
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practical information for working and living in Norway can be found here: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted by
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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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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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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
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Website https://karriere.norceresearch.no/en/jobs/7235739-phd-research-fellow-in-data-a… Requirements Research FieldMathematics » Applied mathematicsEducation LevelMaster Degree or equivalent Skills
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PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements
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dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early