396 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs in Norway
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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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programmes is a primary focus for the faculty's doctoral programme, PhD in educational sciences (UTVIT) (https://www.inn.no/english/research/doctoral-degree/educational-sciences/). It is a prerequisite that
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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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and several centres at Faculty of Science and Technology. Read more about the faculty and departments. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/298034/phd-research-fellow
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in
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period of three years. The position is located at the University of Agder’s Kristiansand campus. The proposed starting date is the 1st of September 2026. About the Faculty: https://www.uia.no/en/about-uia
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models with drone imagery using machine learning techniques and data assimilation. The work will involve collaboration with an interdisciplinary team of researchers, engineers, and local stakeholders in a
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, feasibility and application of theoretical and practical knowledge to better understand how humans have changed ecological systems over the last 6000 years. For more information and how to apply: https
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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