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rearrangements. It will allow progress in the prediction and, eventually, mitigation of their detrimental effect in materials. In addition, it will provide a better understanding of the fundamentals of fast
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) compliance study. · Planning and decision-making in uncertain environments: o AI-based methods o Reactive planning in order to consider driving rules, traffic regulations, etc. o Prediction and
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cellular behavior. This includes generating in silico predictions for biological phenomena that remain inaccessible to direct experimentation. Statistical methods and AI approaches are developed and applied
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 2 months ago
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 of the future ocean state
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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
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will rely on: Developing machine learning-based surrogate AI models (physically informed neural networks) to predict the evolution of calcium carbonate precipitation rates associated with the reduction
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industry, papermaking, or oil extraction. It is essential to be able to predict the flow regimes inside the receiver for two main reasons. First, steam production directly depends on the prevailing flow
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
phenomena. New meta-model architectures based on learning may be proposed and tested on complex EDF use cases. However, this is not sufficient: can such a surrogate, learned from simulation data, predict
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of reduced order to be fast, and connected to data for accuracy, 2) Optimal sensor placement to complete the existing ones and virtual sensors, 3) proactive monitoring and predictive maintenance
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R