41 machine-learning-"https:" "https:" "https:" "https:" "https:" Fellowship positions in Norway
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong
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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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(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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implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned
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cameras, heart rate monitors, and dedicated activity trackers for data collection and employ relevant machine learning methods for data analysis and sensor fusion. The PhD Research Fellow will collaborate
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, and the military. Both quantitative and qualitative approaches would be relevant, and comparative approaches (cross-sector, cross-institutional, cross-national, or other) are welcome, but not required
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Are you ready to take your research career to the next level? The Biopolymer NMR Group (https://folk.ntnu.no/aachmann/ ) is looking for a candidate to be hired for a least three-year postdoctoral position
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economic assessments machine learning or proxy-model based methods field scale simulation geological features geomechanics reactive flow The PhD fellow are not expected to master all these topics. Project
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience