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utilization. DESIRE will equip 15 PhD researchers with cutting-edge expertise in combustion science, chemical kinetics, fluid dynamics, and digital modeling, preparing them to revolutionize industrial energy
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-assisted simulation framework by providing accurate high-fidelity numerical data for training and validation of surrogate models for multi-disciplinary design and optimization. · Participating in
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within fusion reactors, especially plasma-facing materials (PFMs) exposed to intense heat fluxes and energetic particles. Understanding and predicting how these materials degrade under such conditions is
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waves. Understanding energy and scalar fluxes across the air-sea interface is crucial for a number of environmental challenges, including weather, climate and sea state forecasting. The Air-Sea Fluxes
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offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
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tunnel testing and statistical modelling using extreme value theory, the project will yield predictive frameworks for structural risk under rare yet damaging wind conditions. The results will support
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the change! We offer ideal conditions for you to complete your doctoral degree: Competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling
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significantly slows down the development of new desirable nanostructures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA
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data Design algorithms for correlating low-level events into process-level attack models Contribute to joint framework development with TU/e on continual learning Collaborate with industry partners
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We’re looking for a motivated PhD student with a Master’s in Robotics, Control Theory, Applied Math, or Mechanical Engineering eager to work on model-based control of soft robots Job description We