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models, and reinforcement learning (RL), which is data-driven, are two powerful control techniques. MPC techniques are well-established, while RL techniques are gaining popularity due to increasingly
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: Control and operation of distributed energy resources and microgrids Ancillary services and stability of electrical grids Power system simulation using tools such as DIgSILENT PowerFactory and MATAB
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are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates
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industrial processes. Your research will drive a paradigm shift in how TES systems are modelled, integrated, and controlled within industrial settings. You will develop novel, adaptive, physics-informed models
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systems Strong analytical skills and interest in interdisciplinary, real-world problem solving Good communication skills in English and the ability to collaborate with diverse stakeholders You must have a
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/ Computer Science Electricity Markets or Power Systems in addition to solid programming skills (namely Python, Julia) and excellent command of the English language. We welcome candidates with varied experiences and
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in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position. Technology for people