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funding from Petrolia NOCO. About the project/work tasks: The position is affiliated with the project “Reservoir and Seal Characterization & Prediction: An Integrated Workflow Combining Flow-Facies Analysis
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expertise in nonlinear model predictive control. Expertise in numerical optimal control. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work independently
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predictable, complementary renewable source, particularly relevant for coastal nations like Norway. However, the hydrodynamic environment is complex: non-uniform inflows, wave–current interactions, and limited
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in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use
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machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use of artificial intelligence. Electric drilling and other methods
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epidemiological methods, causal inference and machine learning techniques, we aim to: Improve understanding of risk factors for primary headaches Predict diagnosis and disease progression Identify the most
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, utilisation of natural resources, shipping, predictive modelling, or climate risk Core courses in probability and statistical inference, optimisation, microeconomics, scientific methods Elective courses in