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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
Deadline 31 Dec 2025 - 23:00 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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Full-time Hours Per Week 37,5 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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and numerical methods for analyzing stochastic transport equations, which are critical for understanding how random fluctuations affect dynamic systems such as turbulence, water waves, and compressible
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, graduate and post-graduate levels. The Academy hosts almost 400 concerts annually and is at the forefront of artistic development work and research in music. NMH has an extensive concert program and is
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-graduate levels. The Academy hosts almost 400 concerts annually and is at the forefront of artistic development work and research in music. NMH has an extensive concert program and is highly active in
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the Research Council of Norway. The project’s goal is to develop mathematical and numerical methods for analyzing stochastic transport equations, which are critical for understanding how random fluctuations
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theoretical and computational modelling of the droplets and how they wet soft interphases. It is planned that the numerical simulations and theoretical predictions will help advance our understanding
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Profile First Stage Researcher (R1) Country Norway Application Deadline 1 Dec 2025 - 22:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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: The desired candidate demonstrates strong theoretical and methodological capacities as well as documented expertise in computational methods. Documented experience with R or Python programming is also very
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operating conditions and fault scenarios. Development of condition monitoring (CM) solutions by integrating CM data with SCADA and inspection data. Modular performance analytics using SCADA, numerical, and CM