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collaboration with Michelin, is to develop surrogate models capable of rapidly approximating the simulator's results while accounting for uncertainty. Particular attention will be paid to the model's lightness
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
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to fit Ca profiles in olivine and calculate associated cooling rates, 2/ an analysis of uncertainty propagation for these models, and 3/ a global unified database of existing data that could be used
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one of the largest uncertainties in climatic projections and cause millions of deaths worldwide every year. Hence, they have enormous societal and economic consequences. Nonetheless, there is still a
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shortlists of promising molecules with quantitative estimates and uncertainty ranges; and close iteration with experimental partners to validate predictions and refine models. The position also includes