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are applied in real-world settings characterized by large-scale networks, stochastic demand, operational disruptions, and complex constraints. A central research question is how machine learning can be
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Borlaug Faggruppeleder +4799305003 [email protected] Manjana Milkoreit Førsteamanuensis +47922 81 887 [email protected] Where to apply Website https://academicpositions.com/ad/oslo
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global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging
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in one or more of the following research areas is desirable: geometric numerical integration, structure preserving deep learning, stochastic differential equations, generative AI, numerical
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analyses or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of
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team includes: Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning Prof. Mohamed Hamdy – building performance simulation, building automation
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of battery materials in addition to the advanced knowledge in X-ray based characterization techniques. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/305695/researcher-in
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. Applicants must have excellent skills in oral and written English. Fluency in a Scandinavian language is an advantage. All our staff is given the opportunity to attend courses in order to learn Norwegian and
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, knowledge, beliefs, abilities, etc. The project will be conducted within the Logic and Artificial Intelligence (LAI) research group (https://www4.uib.no/en/research/research-groups/research-group-for-logics
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-NorthWind webpage for more details): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer