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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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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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expertise from EO, robotics, computer vision and HPC/HPDA support. DLR also started strategic cooperation with Leibniz Supercomputing Centre, e.g. through recently signed cooperation agreement “Terra Byte
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infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science or a similar field Good theoretical
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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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and distributed systems. Applicants need to have a strong background and interest in algorithms and/or combinatorics. You ideally should have an MSc degree in Computer science with a focus on algorithms
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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