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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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, they are in the same period as the previous year. You can find the current dates here: Application documents The application is submitted in two steps: 1. submission of the application documents 2. submission
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