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17th December 2025 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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knowledge base in applied thermodynamics, mathematical modeling, and modeling, simulation, and optimization of energy systems. To be eligible for admission to the doctoral programmes at the University
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thermodynamics, mathematical modeling, and modeling, simulation, and optimization of energy systems. To be eligible for admission to the doctoral programmes at the University of Stavanger both the grade for your
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, operational, and economic considerations. The research will involve: Mathematical modeling of measurement uncertainty and its impact on decision-making. Physics-based simulations of drilling dynamics under
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technical, operational, and economic considerations. The research will involve: Mathematical modeling of measurement uncertainty and its impact on decision-making. Physics-based simulations of drilling
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at the molecular level. The position is part of the research group for Functional materials and Process chemistry at UiS, with partners such as SINTEF and USN. Qualification requirements The applicant must have a
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analysis using advanced instrumental methods. The project will also include collaboration with researchers who model adsorption processes at the molecular level. The position is part of the research group
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of Innovative Universities. The university is located in the most attractive region in the country with more than 300,000 inhabitants. The Stavanger region has a dynamic labour market and exciting cultural and
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. The university is located in the most attractive region in the country with more than 300,000 inhabitants. The Stavanger region has a dynamic labour market and exciting cultural and leisure activities. Together