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- NTNU - Norwegian University of Science and Technology
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communication technology that facilitates the use of protection and control systems in the substation. In digital substations the tasks of upgrading, operating, and maintaining the large number of protection
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Cybernetics at NTNU is offering a fully funded PhD position in the area of learning-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks
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communication technology that facilitates the use of protection and control systems in the substation. In digital substations the tasks of upgrading, operating, and maintaining the large number of protection
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, this research project will focus specifically on how multiple grid converter-interfaced assets should be controlled and coordinated in an inertia-less (or almost inertia-less) isolated power network, to ensure
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/SinglePageApplicationForm.aspx… Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications Professional skills Experience in: Reinforcement Learning (RL), Model Predictive Control (MPC
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command of a Scandinavian language is an advantage but not a requirement. In addition, experience from research projects and publishing in academic journals will be an advantage. General criteria
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the field of optics. The research group conducts applied research in fields such as remote sensing, communications technology, autonomous platforms, power electronics, energy systems and advanced control
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the maritime industry and/or maritime logistics Command of Norwegian or another Scandinavian language is an advantage, but not required Personal characteristics To complete a doctoral degree (PhD), it is
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Academically relevant background within marine control/cybernetics, computer science, or hydrodynamics, with good skills in mathematics, programming, and machine learning. Master's degree in control engineering
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Academically relevant background within marine control/cybernetics, computer science, or hydrodynamics, with good skills in mathematics, programming, and machine learning. Master's degree in control engineering