152 parallel-and-distributed-computing-"Meta"-"Meta"-"Meta" positions at Technical University of Munich in Germany
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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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scientific work on design automation for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. One of the main challenges in
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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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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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://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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, and computation Excellent communication skills in spoken and written English Our offer Remuneration and benefits in accordance with the collective agreement for the public service (TV-L E13
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finite elements) as well as alternative discretization methods (e.g., Lattice Boltzmann Methods), and high-performance computing. A selection of possible research areas can be found on our website: https
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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