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for resilient manufacturing systems. This topic will build upon existing theory on modular and reconfigurable manufacturing systems and develop methods and model-based approaches to design and evaluate resilient
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, probability theory, and combinatorial optimization. Experience in decision-making under uncertainty and autonomous system operation. High level written and spoken English skills. You may obtain further
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strain theory and advanced hyper elastic material models incl. anisotropy You preferably have insights into topology optimization and/or finite element analysis and are committed to improving state
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assembly, disassembly, and quality management. The position is available as of May 1, 2025, or as soon as possible thereafter. The workplace is the SDU Campus Odense, with some travel required within Denmark
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include Master’s-level in Mechanical Engineering, Aerospace Engineering, Control Engineering, Wind Energy, or a closely related field. Strong background in control theory, fluid dynamics, structural
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theory around the pace-of-life of marine fish and simulate fast and slow life history strategies within fish populations and fish community food webs. This research aims to examine how these strategies
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on the most advanced theories, models, using first-hand cases and data from the wind energy industry, to lift our understanding of wind and wave characteristics during storms in the presence of wind farms
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on novel high-resolution microscopy techniques to experimentally quantify transition probabilities, alongside density functional theory (DFT) calculations of defects in feldspar. This inter-disciplinary
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strong multi-disciplinary focus on energy markets, optimisation, game theory, control and machine learning. The EMA section (https://wind.dtu.dk/research/research-divisions/power-and-energy-systems
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, theory, and methods of the PhD project is up to the candidate. It is highly recommended that interested candidates contact one of the project leads to discuss their PhD proposal prior to application