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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
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Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. The University of Stavanger funds the position. It is connected to the international research project
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
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University of Stavanger invites applicants for a PhD Fellowship in in molecular modelling and machine learning for improved subsurface utilization, at the Faculty of Science and Technology, Department
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The position A position in knowledge-driven machine learning is available at the Department of Physics and Technology , Faculty of Science and Technology, within the UiT Machine Learning Group . This position is
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integrated circuits (PIC). An optical set-up will be used to characterize the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis
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Stig Brøndbo 22nd October 2025 Languages English English English Faculty of Science and Technology PhD Fellow in Knowledge-Driven Machine Learning Apply for this job See advertisement The position A
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Additional Information Work Location(s) Number of offers available1Company/InstituteDepartment of Electrical Engineering and Computer ScienceCountryNorwayGeofield Contact City STAVANGER Website http
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Work Location(s) Number of offers available1Company/InstituteDepartment of Electrical Engineering and Computer ScienceCountryNorwayGeofield Contact City STAVANGER Website http://www.uis.no Street 4036