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, or examples, these aspects are of utmost importance and need to be explored to provide convincing and well-grounded arguments [1]. This PhD program will propose to explore advanced methods to detect implicit
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of operators. The objective of this postdoctoral project is to develop methods and systems for the efficient, reliable, and task-specific execution of workflows involving LLMs, with a primary emphasis on
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Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
) appendage shape or LA morphology, have recently emerged as valuable predictors of stroke risk. However, they do not integrate blood flow characteristics responsible for thrombogenesis. Methods Two main
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their dynamics to be formulated as systems of linear ordinary differential equations. Bayesian Optimization and Reinforcement Learning methods will be employed to solve the inverse problem of shape and flexibility
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for magnitudes between 7 and 8. Research program The project will aim to adapt PEGSGraph (Juhel et al., 2024), a graph neural network we designed for rapid magnitude estimation from PEGS (Hourcade et al., 2025) in