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estimation, and performance prediction. Build computationally efficient models suitable for monitoring, performance prediction, optimization, and control, and evaluate their accuracy, robustness, computational
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for Applied Power Electronic Systems. You will join an interdisciplinary team working across electrolysers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization, in
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team working across electrolyzers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization, in close collaboration with the Technical University of Denmark (DTU
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for Applied Power Electronic Systems. You will join an interdisciplinary team working across electrolyzers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization, in
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dynamics, control algorithms and sensor integration can be designed as a coherent system to improve speed, range, maneuverability, response time and operational robustness while also having underwater
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increasingly accurate controller design. A central part of your work will be the development and assessment of advanced control structures and control methods that ensure robust and efficient operation of
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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support recipe optimisation for well-controlled materials and processes, you will investigate whether similar methods can be applied to mechanical recycling from heterogeneous waste streams. The ambition is
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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years. Your work tasks This PhD project focuses on the design and control of energy-efficient hydraulic systems with integrated safety functionalities. The overall objective is to develop innovative