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-level decision-making, it does not address the strategic optimization of fleet-wide renewal plans under uncertainty—a critical need for organizations aiming to decarbonize cost-effectively and in
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven
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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
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, · quantifying uncertainty in causal links, · integrating the resulting models into neural networks (or other machine learning models) to detect and predict anomalies or anticipate failures. The research