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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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. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning. Your tasks: Development and comparison of data driven models for the prediction of stresses in
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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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the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and
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submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and regression models to isolate task-related submanifolds and their respective role for sensory processing and task
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an impact in a societally relevant application In your application, please include a statement of research interest, CV, copies of exams, degrees and grades (transcript of records), a copy of your Master
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the West Bank in the following fields of postgraduate programmes (please pay attention to the different language requirements, see below): Al-Quds University M.Sc. Biochemistry and Molecular Biology M.Sc