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are offering a fully funded PhD position in the field of Physics-informed Learning-based Control. This interdisciplinary research area bridges control theory, machine learning, and physics-based modeling
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of imaging data such as structural MRI and functional MRI, preferably ultra-high field imaging is required Experience in machine learning methods and analyzing big datasets is desirable Experience in
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that combine principled reasoning with the efficiency of modern machine learning to enable intelligent, real-time decision-making in large-scale interconnected systems. This position offers the opportunity
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to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
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-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks that combine principled reasoning with the efficiency of modern machine learning
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Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning) or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120
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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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approach of data-driven membrane discovery that includes material space construction and exploration, candidate selection and verification, providing data for machine learning models to optimise membrane
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for the position. Preferred selection criteria Scientific publications are an advantage Experience in research project works Good knowledge and experience in the use and development of machine learning algorithms
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. Required selection criteria Experiences with Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA) and Mass Spectrometry (MS) Good programming skills for scientific post-processing