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15th January 2026 Languages English Norsk Bokmål English English PhD Fellowship in molecular modelling and machine learning for improved subsurface utilization Apply for this job See advertisement
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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 Integreat community whose members are in Tromsø and Oslo. Your role as a PhD Fellow You will be an integral part of Integreat via the UiT Machine Learning Group. You will engage in collaborative research with
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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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English English PhD Research Fellow in Machine Learning and Distributed Data Processing Apply for this job See advertisement Job description Position as PhD Research Fellow in Machine Learning and
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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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. 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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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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by integrating petrophysics, rock physics, geophysics, geomechanics and machine learning. A detailed project plan will be developed in collaboration with the successful candidate at the start of PhD
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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