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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
, preferably in seal/reservoir/overburden heterogeneities, static and dynamic reservoir modelling, and flow simulation. The candidate will work in a team of geologists, geophysicists, geochemists and staff with
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scientists, and we put emphasis on communicating our research to decision-makers and a wider audience. Our methods include global and regional modeling of human and natural systems, the use of observational
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and dynamic reservoir modelling, and flow simulation. The candidate will work in a team of geologists, geophysicists, geochemists and staff with strong machine learning and numerical modelling
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engineering, ICT, computer science or a similar/related field. System safety and security engineering. Simulation and modeling for industrial systems. Technical expertise in the following areas: Background in
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model by integrating the newly developed approaches into the numerical program developed in the ‘OceanCoupling ’ project. We would like the successful applicant to start in the first quarter of 2026
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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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geoscience knowledge, preferably in seal/reservoir/overburden heterogeneities, static and dynamic reservoir modelling, and flow simulation. The candidate will work in a team of geologists, geophysicists
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focused on digital tools and methods for urban planning and decision-making. Develop and apply computational urban models, simulations, and data-driven frameworks to support urban policy and planning
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systems and models to enhance learning through AI technology. The Postdoc fellow will engage with developing models, frameworks and technologies that facilitates more efficient development of rich