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simplification. Particular attention will be paid to uncertainty quantification and to the definition of criteria that assess the contribution of each simulation to the improvement of the prediction
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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for geophysical flow modelling, uncertainty quantification, and high-performance computing. Its work relies on both deterministic and statistical approaches. The objective of this PhD project is to develop a new
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