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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 16 days ago
to intertwine a multi-contact whole-body controller, a digital simulation of the interacting humans, and machine learning models to predict and respond to human movements and intentions. In a crescendo of
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predictive control, optimization-based decision frameworks, and data-driven performance modelling. The overall goal is to develop computational methods that enable efficient and intelligent operation of wind
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design strategies, while producing structured spatio-temporal datasets that will serve as input for realising predictive models. Objective 3 — Realize predictive tools for scenario-based assessment
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induced seismicity. Current models remain limited by the scarcity, heterogeneity, and noise of available data, as well as by incomplete knowledge of the subsurface. Physics-Informed Neural Networks (PINNs
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, updated 2025/11/03, listed until 2026/05/16 04:59 AM UnitedKingdomTime) Position Description: Apply Position Description The Center for High Order Plasma Turbulence Modeling for Z-Pinch (HighZ: https
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and machine learning based analyses including predictive modeling and real world evidence generation. Basic Qualifications: MS in computer science, biostatistics, biomedical informatics or related field
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integration of the SUMMA system for hydrological predictions. Application of the models to the Alcácer do Sal region, located in the Setúbal District Contribute to the development of a prediction and forecast
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, for the project “PREDICT-OAE project (From data to PREDICTion: modelling temporal ecological–biogeochemical links under Ocean Alkalinity Enhancement”, financed by internal funds from CIÊNCIAS and FCiências.ID
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physical agent-based models, as well as the integrations of omic information to validate model predictions and developed in the context of the HPC environments at the BSC and at other HPC centres in Europe
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model biases, and identify sources of predictability. The project will involve; 1) rigorous interrogation of NOAA GFDL's CM4X simulation output with respect to coastal sea level variability and relevant