191 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
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, investigates how children and adults actively seek, select, and evaluate information to learn about the world. The lab combines behavioral, computational, and cross-cultural approaches to study curiosity
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of Orthopaedics and Sports Orthopaedics and the Institute for AI and Informatics in Medicine. We work at the intersection of artificial intelligence, medical imaging, and clinical practice, developing methods
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low-molecular compounds, e.g. interactions between plant proteins and starch, are to be elucidated by combining methods of modern, instrumental natural product analysis with biophysical techniques
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(WNVI) framework and aims to advance its capabilities in the following directions: • Scalability: Extending methods to high-dimensional and three-dimensional elastography problems using neural operator
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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entrepreneurship education Data-driven optimization: Establish a systematic assessment and mapping of TUM's entrepreneurship education components to talent journeys Program development: Contribute to strategic
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/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and
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of rainfall, drainage capacity, and 3D urban form on flood severity • Validate results with hydrodynamic simulations and 3D urban semantic models, benchmark against state-of-the-art methods, and publish in
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methods in AI and machine learning, contributing directly to state-of-the-art research with high industrial relevance. Your Qualifications A strong background and Master's degree in Computer Science, AI
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for safety-critical bilateral teleoperation. The research will leverage a combination of passivity-based control methods and machine learning techniques to enable reliable and robust teleoperation in uncertain