80 computer-programmer-"Multiple"-"U"-"Prof" positions at Technical University of Munich in Germany
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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for benchmarking, HPDA/HPC support, and education (e.g. MOOCs, organizing workshops, facilitating community building). Requirements: Completed university degree in computer science or applied mathematics, remote
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master’s degree in Computer Science, Computational Linguistics, Natural Language Understanding, or similar Very good programming knowledge, preferably in Python Experience with state-of-the-art machine
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random
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-quantum cryptography and coded computing (1 postdoc, 1 PhD, Antonia Wachter-Zeh, antonia.wachter-zeh@tum.de) • Theory for communication systems beyond Shannon's approach (1 postdoc, 1 PhD, Christian Deppe
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08.04.2022, Wissenschaftliches Personal Development of Lattice-Boltzmann solver, programming in C/C++ and CUDA, implementation on GPU cluster, testing of real-time capable software on flight simulator, collaboration in LuFo project, The Chair of Helicopter Technology at the Technical University...
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of ML for Earth observation will be supported. Requirements: PhD in computer science, geoinformatics, data science, business administration, or comparable field of study professional experience in Earth
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. Detection and imaging of electrical signals in neurons, the cells performing computation in our brain. You will work towards this goal by one of two complementary approaches: testing new quantum materials
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near Munich in Germany. If your goal is to explore novel approaches to advance superconducting quantum computing, we would be happy to receive your application. We are looking for a skilled candidate
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, agriculture science or related fields (Science: Biology, Computer Science, Data Science, Agricultural Economics etc.; Engineering: Mechanical, Electrical, Bionics, etc.) 3. Programming knowledge for AI