146 computer-programmer-"IMPRS-ML"-"IMPRS-ML" positions at Technical University of Munich in Germany
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writing. Drive the publication of research results in top-tier robotics conferences and journals. Requirements Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, or a
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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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representations. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing
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for the School’s PhD program. We offer regular public lectures and symposia, weekly discussion groups, and visiting researcher programs. We maintain close collaborative ties to other parts of TUM as
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accessible to users from science and industry Your qualifications: ■ Master’s or equivalent graduate degree in computer science, artificial intelligence, machine learning, mathematics, statistics, data science
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representations. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing
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leading international journals and conferences • Literature research • Scientific publishing Your qualifications: • Completed academic university degree (university diploma / M.Sc.) in Computer
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prestigious Humboldt Research Fellowships for the Logistics and Supply Chain Management research group at TUM School of Management. With the scouting program, the foundation aims to attract highly talented
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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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, static user representations, and data sparsity. While deep learning models offer improvements, they often come with high computational costs and require frequent retraining, which limits their scalability