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complex real-world data structures. Probabilistic graphical models (PGMs) have been well developed in recent years to mathematically model real-world scenarios in compact graphical representations
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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AI researchers from ANITI, IMT and CERFACS, as well as with researchers/engineers in weather forecastings from the CNRM (Météo-France). Hybridization methods between neural networks and physical models
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by the Simons Foundation’s grant ``Probabilistic paths to Quantum Field Theory’’, started on September, 1st 2025 https://probabilistic-qft.org/ . Applicants must hold an excellent master’s degree in
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) relationship with the low-fidelity response. Extensions include nonlinear information fusion with GPs, Bayesian multi-fidelity inference and deep probabilistic surrogates, as well as MF neural networks
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human activities, and a probabilistic analysis of the risks associated with their development by 2050. 1. Literature review of multi-scale modelling methods for cumulative effects Initially, a
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of potential seismic sources, with a view to integrating these findings into deterministic or probabilistic seismic hazard assessments (see Jomard et al., 2017). This PhD project will be carried out in close
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machine learning e.g., GNNs, graph representation learning, hierarchical or probabilistic graph models Strong analytical and problem‑solving abilities, with enthusiasm for developing novel computational
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burner Related Bibliography : [1] «Advisory Council for Aviation Research in Europe. Strategic Research Agenda» web . [2] AIRBUS, «Aviation industry growth forecast 2021 - 2040,» 2021 web . [3
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methods for quantitative characterisation and forecasting of deep fluid circulation" (task leader: R. Chassagne) within the "PEPR sous-sol bien commun PC9", and will therefore use data from the Rhine Graben