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learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
with setting up a streamflow forecasting system in Portugal and the advancement of scientific knowledge in machine learning probabilistic hydrological forecasting and decision-making optimized to act on
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weather forecasting to cardiovascular medicine. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning
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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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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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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and
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: 12 January 2026 Apply now Are you eager to jump-start your career in Differential and Probabilistic Programming? As a PhD candidate in the ERC project FoRECAST, you’ll work independently and in a