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must hold a Master degree in Electrical Engineering (or equivalent), have a solid mathematical background (e.g. in control theory and optimization) and have taken specialized courses in at least one of
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on developing data-driven, low-order aerodynamic models of VPPs, updated in real time with experimental data, and using them to design control strategies for flight stability and performance optimization
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Electrical Engineering (or equivalent), have a solid mathematical background (e.g. in control theory and optimization) and have taken specialized courses in at least one of the following disciplines: advanced
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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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farm layouts with high specific power density through the co-optimization of array design and control strategies. This project is a collaboration with CNR-INM Institute of Marine Engineering in Rome
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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. The central aim is to design intelligent systems that dynamically adapt the environment to support optimal learning conditions, based on real-time neurophysiological feedback. Key principles guiding