148 parallel-and-distributed-computing-"Meta"-"Meta" positions at Technical University of Munich
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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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25.08.2025, Wissenschaftliches Personal The Chair of Architectural Informatics at the Technical University of Munich is looking for a research associate (m/w/d) for the research in the frame
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
of Munich (TUM), Campus Heilbronn. We are looking for exceptional candidates who are interested in pursuing a PhD in either theoretical computer science or graph and network visualization. We seek PhD
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academic assignments at the chair What we look for in you Completed master’s degree in computer science, transportation, or related engineering fields Solid background in generative AI, machine learning, and
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an interdisciplinary career skills programme across Europe. The Technical University of Munich (TUM) is one of the best universities in Europe. It is characterised by excellence in research and teaching
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for 3 - 6 years, with the option to enter the habilitation program in the format of 3 + 3 years. The salary will be determined according to the German collective wage agreement in public service (TV-L 13
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://mediatum.ub.tum.de/doc/1687691/ltbbjgwihiht96fqfeblxdyj7.ITSC22_CommonOcean.pdf Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines
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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