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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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on model behavior. We will divide our work into three thrusts: Thrust A: A first major objective will be to augment classical spike train analysis methods particularly those developed by Prof. Grün and
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