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Field
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The postdoctoral fellow will participate in the PostGenAI@Paris AI Cluster (ANR) project at Sorbonne University, and more specifically in the "AI-Augmented Multiscale Modeling for Energy Storage" sub-project, whose
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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assess rank and identify the most promising fields for cyclic hydrogen storage such that they can be assessed in more detail using traditional reservoir characterisation, modelling, and simulation
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their scales, exploring parameter space for vortex behaviour using theory and idealised model simulations, testing the relevance of the new paradigm using case studies observed using during the NERC
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to unravel the atmospheric importance of this interfacial chemistry by means of (i) laboratory-based investigations, (ii) field observations and (iii) modelling. These activities will take place in the frame
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and implemented in Fenics to: - Identify the mechanical properties of collagen hydrogels, depending on their manufacturing conditions, based on experimental data. - Improve these models to include
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 9 days ago
opens the way for uncovering them using data-driven techniques and bridge the gap between constitutive modelling, numerical simulations, and experiments. As a Postdoctoral Researcher, you will explore and
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 7 hours ago
, fiber-specific models are needed to simulate fiber contacts within the weave hierarchical geometry (fiber to tow to yarn to weave) and the inherent directionality of fibers. In woven thermal protection
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"agent mind" capable of integrating multidisciplinary knowledge to assess task understanding, predict actions, and evaluate teamwork competencies. Validate and test these models in simulated and/or real
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sequences for predicting disease progression and outcomes; Developing advanced generative models to simulate patient health trajectories, including disease progression, based on real-world data, enhancing