19 machine-learning-"https:"-"https:"-"https:" Fellowship positions at University of Stavanger
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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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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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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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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 acquired strong
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have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within generative artificial intelligence to medical images and
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the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic The PhD Fellow will join the research group in risk management and
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plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic The appointed
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with research duties exclusively. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral