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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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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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personal data is saved by the DAAD in accordance with the Federal Data Protection Act and with the EU Data Protection Regulation insofar as this data is needed to process the application. Submitting
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with the DAAD. Your personal data is saved by the DAAD in accordance with the Federal Data Protection Act and with the EU Data Protection Regulation insofar as this data is needed to process the
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the DAAD in accordance with the Federal Data Protection Act and with the EU Data Protection Regulation insofar as this data is needed to process the application. Submitting an application General information
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industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future
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Sciences** M.Sc. Computer Science** M.Sc. Data Science** M.Sc. Physical Therapy** M.Sc. Nursing - Adult Acute Care** M.Sc. Nursing - Community Health Nursing** M.Sc. Nursing - Nursing Services Administration
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the fields of medicine, biology, chemistry, physics, technology, and the humanities. Since 1948, MPI researchers have been awarded 21 Nobel prizes, which testifies to the quality and innovation of MPI research