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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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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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to: compositional multiphase reservoir simulation upscaling or screening methodologies optimization of well positions and control strategies economic assessments machine learning or proxy-model based methods field
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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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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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integration and optimized operation using machine learning and AI techniques as key drivers for improving system performance. The hired candidate will have the opportunity to work with cutting-edge energy
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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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that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic Over the past years, University of Stavanger has