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develop a new generation of hybrid models combining large-scale machine learning with physical knowledge to represent interactions between mobile robots and their environment. The research will address
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. As the threat of future pandemics driven by novel influenza strains, coronaviruses, or yet-unknown respiratory viruses remains very real, there is an urgent need to develop flexible, pathogen-agnostic
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models enabling the prediction of browning intensity during storage. Missions The recruited person will be responsible for: Study of reaction dynamics during simulated drying development and use
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will develop a mathematical framework connecting these two systems. Starting from minimal nonlinear dynamical models, the student will investigate state-space structure and attractors, local stability
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particularly welcome candidates who enjoy discovery-driven research, are comfortable developing experimental approaches, and are motivated by projects in which the most interesting results may emerge from
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interconnected and closely intertwined scientific themes. The first targets the development of hybrid algorithms combining multi-physics modelling of electronic components, predictive control and machine learning
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description SuperNEMO project is driven by an international collaboration of a hundred
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interpreted within a THMC physical modeling framework, in which deformation controls the evolution of permeability, fluid pressure evolves via porous flow, and reactions (serpentinization) modify bulk and
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 2 months ago
this large panel of skills, the team aims at improving our understanding, reconstruction and forecasting of ocean dynamics, and more specifically to bridge model-driven and observation-driven paradigms
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 2 months ago
observation-driven paradigms to develop and learn novel representations of the coupled ocean-atmosphere dynamics ocean models. For accurate climatic predictions, it is essential to have plausible forecasts