78 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" Fellowship positions in Norway
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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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intelligence/machine learning skills. The candidate’s research proposal must be closely connected to the call and the research of NCEI. Excellent skills in written and oral English. Personal suitability and
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groundwater/geochemical modelling software (e.g., MODFLOW, PHREEQC). Experience with laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications
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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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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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refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
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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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, including individually tailored career development plans with formal supervision and project-based learning. Secondments, consortium meetings, and workshops will provide hands-on experience in collaborative
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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