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, power conversion, energy and hydrogen storage, downstream processes, and energy demand, to enable more efficient, flexible, and economically viable Power-to-X operation. This position is expected to start
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capabilities. Particular emphasis will be placed on high-speed USV operation in realistic marine conditions, where propulsion, control and sensing are strongly coupled. PhD Focus Area: Propulsion, Control and
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designed according to their value for the task being performed. The project will combine fundamental research in wireless sensing, communication, and networking with AI-driven inference and robotic
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different feedstock compositions and processing conditions influence performance, and to evaluate the ability of the models to serve as robust tools for dynamic recipe design in real production environments
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optimization, techno-economic assessment and model validation. The research will also examine the coordinated operation and control of Power-to-X processes, electrolysers and energy-storage systems in
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solutions that combine low energy consumption with reliable and safe operation in compliance with relevant standards and regulatory requirements. A key scientific challenge addressed in this project is the
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defining limit values suitable for use in LCA-based frameworks. The work may also address targets such as climate neutrality, net-zero, and regenerative performance, as well as methodological challenges
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system configurations, experimental setups and operational data. The scientific ambition is to develop methods that combine physical models and data-driven approaches for adaptive, real-time operation of
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, interdisciplinary working environment In-house modelling, data processing and data assimilation expertise, software, and High Performance Computation (HPC) infrastructure Excellent scientific infrastructure
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grow in complexity and scale, traditional monitoring approaches are insufficient to ensure efficient, reliable, and fault-free operation. This project will develop novel AI methods that bridge first