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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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, Robotics, Computer Science, Statistics, or related discipline. Strong background in Machine Learning and Control Theory. Demonstrated experience in research projects with industrial partners. Excellent
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, making use of economic theory and state of the art econometric methods. The Department of Economics has a strong research-oriented faculty working within microeconomic theory, macroeconomics, econometrics
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, making use of economic theory and state of the art econometric methods. The Department of Economics has a strong research-oriented faculty working within microeconomic theory, macroeconomics, econometrics
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to contribute to foundational research at the intersection of control theory, optimization, and artificial intelligence, with potential applications in energy systems, and infrastructure networks. The successful
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to enable intelligent, real-time decision-making in large-scale interconnected systems. This position offers the opportunity to contribute to foundational research at the intersection of control theory
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engineering and information technology, protection automation and control theory studies. The PhD candidate will address new protection, control, and automation concepts development, understanding important
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. Project description (max 6 pages), including a summary and references, using this template . Please include area of research, research problems/questions, methods and use of theory CV (max 3 pages). Use
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theory studies. The PhD candidate will address new protection, control, and automation concepts development, understanding important mechanisms for substation protection using digital technologies both in
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be met: Advanced methodological knowledge in the form of completed master's course or documented exam in methods / theory of science at master's level A Scientific article assumed in a peer-reviewed