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, optimization techniques, and climate change scenario analysis. The successful candidate will contribute to the development of intelligent models and decision-support tools that enhance the performance
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computational models for trustworthy applications in critical care. The doctoral position is part of the research initiative “The Digital Society” at ØUC. Project description Intensive Care Units (ICUs) generate
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combination with multi-fidelity response models. The multi-fidelity models may include combinations of physics-based response models, Artificial Intelligence (AI) models and probabilistic methods. Your
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of buildings by combining simulations with experimental data investigate human comfort based on the experience of the occupants of buildings building information modelling and digital twins development of user
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and develop frameworks and knowledge on planning and coordination of resources within and across projects. apply quantitative methodologies, such as simulation and analytical modelling, to develop
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relevant component development tasks in the project Contribute to relevant simulation and modelling activities in the project Required selection criteria You must have a professionally relevant background in
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participate in the planning and running of experiments and be in charge of analyzing data from experiments, as well as performing modeling work of the phenomenon. The candidate will collaborate closely with