573 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" positions in Norway
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hypotheses related to metabolic rate increases, energy allocation shifts, temperature-dependent bioaccumulation, and varying toxicity across biological levels. For more information and how to apply: https
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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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Energy and Environmental Economics, focusing on macroeconomic analysis of energy transition policies
in Norway. About the project This PhD position is part of the newly funded VISTA Centre for Norwegian Transformative Energy Policy Development (NOTRAP) (https://www.ntnu.edu/notrap ), which will
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Interaction (HCI). The position will collaborate closely with (1) the NTNU Shore Control Lab (SCL), a design and human factors research environment focusing on human-centered design of technology for safety
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. The applicant must have an academically relevant education corresponding to a five-year master’s degree or a cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian
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-supervised by Prof. Marianne Fyhn: https://www.mn.uio.no/ibv/personer/vit/rafalc/ https://www.mn.uio.no/ibv/english/people/aca/mariafy/ Jarli og Jordan/UiO via Unsplash Jarli og Jordan/UiO What skills
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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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, 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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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