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Technology, and the PhD student will be positioned in the Esbjerg Energy section. The position is part of the internally funded research project SURGE: Speed-optimized USVs for Robust Guidance and Offshore
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their accuracy, robustness, computational efficiency, and practical applicability. They could also be implemented in real-time systems. Investigate interactions across operational timescales (Multi-timescale
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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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methodological research with robust software implementation and real-world deployment in a large international research infrastructure. Relevant research directions include, but are not limited to: Agentic AI
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relationships between powder composition, microstructure and instant functionality, ultimately providing new strategies for designing dairy powders with faster, more reliable and more robust reconstitution
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is desirable. Familiarity with optimal, robust, or adaptive control approaches, particularly multi-objective formulations balancing energy performance and structural loads, will also be beneficial
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safety functions directly into the system design, ensuring stable and robust operation without compromising overall efficiency. A central component of the project is the design, implementation, and
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service, and education contribute to the development of a sustainable blue bioeconomy, robust aquatic ecosystems, and reduced effects of climate change. We have a large national and international network
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be considered an advantage if you have experience with safety-critical systems, multi-agent autonomy, or learning-based/data-driven/robust/adaptive control under uncertainty, supported by strong