56 parallel-and-distributed-computing-"Multiple" uni jobs at Technical University of Munich in Germany
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that eventually will automate crucial design steps. In addition, we are developing simulators (on various abstraction levels; using, e.g., Computational Fluid Dynamics) which enables us to validate designs
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of computer vision and machine learning methods for automated analysis and processing of multimodal remote sensing data. About us The Technical University of Munich (TUM) is committed to excellence in research
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simulators (on various abstraction levels using, e.g., Computational Fluid Dynamics) which enables us to verify designs of microfluidic devices even before the first prototype is fabricated. Fabrication: We
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very good master's degree in a topic-related field (computer science, automotive engineering, electrical engineering) Experience in scientific work, project acquisition as well as management experience
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technical field, such as mechanical engineering, computer science, transportation systems, or civil/environmental engineering with a focus on traffic engineering, with very good grades. You bring solid
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. Contact Prof. Holger Boche, Technical University of Munich, School of Computation, Information and Technology, Chair of Theoretical Information Technology, Theresienstrasse 90, 80333 Munich. https
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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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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