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field) and ground-based (radio) data - Use of various software codes: (i) radio emission simulation code, (ii) solar wind propagation code. - Development of software (preferably in Python) for data
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selecting simulations to run based on a given prediction objective. • Implement and validate these developments in the YALES2 code. • Utilize high-performance computing resources to run the simulations
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interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The
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the carbon emission of modern production lines via operations management requires multiple coordinated tasks ranging from detection, diagnosis, prediction, solution recommendation, and efficient monitoring
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of numerical models to study acoustic and optical interactions in metasurfaces, using in-house codes and COMSOL Multiphysics software. 2. Geometry and Material Optimization: Systematic exploration of structural
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
. Preferred qualifications include experience with: Optimal Control and/or Model Predictive Control (MPC). Modeling of deformable parts. Real-time numerical optimization. LanguagesFRENCHLevelBasic
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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
, but current strategies to identify patients in whom it will be beneficial lack efficiency. Aim The main goal of this project is to develop innovative point of care tools for the prediction and
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
simulations are a key tool for testing scientific hypotheses and predicting the evolution of these systems. However, their computational cost remains prohibitive, particularly at large spatial and temporal
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-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build trustworthy and robust AI models that address domain-specific challenges in
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. Finally, a multiphysics tribology-materials-corrosion model will be developed and implemented in a wear prediction code capable of predicting the evolution of wear depth in either the 316LN tube or the 304L