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- University of Oslo
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Field
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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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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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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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simulations of planet formation through N-body simulation, focussing on models of planetesimal and pebble accretion. Additionally, it requires the implementation of different disk models and formation
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discovered exoplanets and exoplanetary systems as compositional and dynamical guide. This includes conducting numerical simulations of planet formation through N-body simulation, focussing on models
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planet. This work will build upon our previous work and shall incorporate new disc models for N-body simulations of planet formation. The work is carried out in collaboration with the PhD fellow, who is
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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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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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Habitability and linked to the “Galactic Recipe for Exo-Planets” (GREP) project funded by the Research Council of Norway. GREP’s objective is to take exoplanet and exoplanetary system formation modelling
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-language generative modalities, with a strong emphasis on visual media, to achieve high cultural fidelity, developed with and for Sámi communities. The research advances methods, models, and evaluation