99 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Norway
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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, using N-body simulations to simulate structure formation and connecting the simulations to observables. The candidate will also be working with machine learning techniques to develop emulators
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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 should be used in this context
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embedded in a multidisciplinary research environment combining expertise in machine learning (ML), numerical modelling, satellite remote sensing, and Arctic geosciences. The Centre is actively involved in
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(PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. Place of work is the Department of Mathematics, Blindern
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, Machine Learning or Deep Learning to investigate transport justice and mobility inequalities with real use cases. Develop theoretical frameworks of mobility justice principles into computational models
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machine learning with focus on risk-sensitive decision making and control. Techniques may include forward, backward stochastic differential equations, stochastic partial differential equations, stochastic
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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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
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of GIS, spatial statistics, or other spatially relevant methods. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with