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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 19 days ago
intelligence is growing at a fast pace, the bulk of the world's computing power remains targeted at modeling and predicting physical phenomena, such as climate models, weather forecasting, or nuclear physics
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regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty bounds and deriving
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of linguistic corpora, the development and use of Machine Learning and Artificial Intelligence models for the prediction, categorization, and automatic evaluation of pragmatic aspects of language, up
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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9 Feb 2026 Job Information Organisation/Company Université Gustave Eiffel Research Field Computer science » Modelling tools Engineering » Electrical engineering Researcher Profile First Stage
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be defined at two levels: SAACD Component: This is a UAV made up of hardware and software sub-systems, capable of observing, predicting, deciding and reconfiguring itself to fulfil its mission (e.g
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
Automata (CAFE) to considerably reduce calculation times and improve the response of numerical models. The numerical models will include laser-matter interaction, melt, and microstructure prediction models
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models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to rupture, which is one cause of a stroke and thus the prediction of plaque rupture is very
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processes, targeting annual savings of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real
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profiling of patient samples is essential to predict responses, identify candidate biomarkers and personalise therapy aimed at harnessing the immune system to target the tumour. This is a challenging