325 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" Fellowship positions in Norway
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machine learning. Colourbox via Unsplash Colourbox What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities
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publications and to contribute to a rapidly evolving field. For more information and how to apply: Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/295728/postdoctoral-research-fel
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teaching and learning. The Faculty consists of six departments as well as a Faculty administration. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/296315/postdoctoral-fellow-in-mo
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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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over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied to machine learning algorithms in order to get uncertainty estimates for parameters governing
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, the Hospital Pharmacies Enterprise in South-Eastern Norway and the Medicines Optimization Innovation Centre, Nord-Irland. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job
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, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies (mAbs) used in autoimmune, inflammatory, and neurological diseases. Using
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large datasets analyses Active participation in LALP Lab activities Required selection criteria You must have completed a doctoral degree in cognitive science or computer design/programming Training and
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across the University of Oslo, industry partners and University College London (UCL). The successful candidate will work with and further develop the electricity system model highRES to analyse the role
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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