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around us evolve over both time and space, making spatio-temporal processes and data omnipresent in science and technology, with applications ranging from weather forecasting to cardiovascular medicine
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to cutting-edge research at the intersection of artificial intelligence, multi-modal data fusion, and probabilistic risk assessment of infrastructure under extreme hazard events. This position offers
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drought forecasts. This project has a firm end date, thus requiring a researcher who with direct probabilistic drought outlooks research experience to advance the project research quickly. Funding
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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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-du-Lac, Savoy. The lab is organised in three research teams: EDPs2 (partial differential equations: deterministic and probabilistic studies), Géométrie (Geometry), and LIMD (Logic, Computer science
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focuses on developing principled, scalable, and efficient methods for modeling complex temporal dynamics, with applications in probabilistic forecasting and data imputation. Possible research topics include