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languages used: C++ 2014, CUDA, Lua Desirable: - interest in high-performance computing with graphics processors (GPUs) and simulation methods - fluent knowledge of modern C++ and a scripting language
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mathematics, e.g., probability theory, linear algebra, differential/integral calculus Prior programming experience in Python is a must, C++ and CUDA experience are a plus Hands-on experience in working with
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one of the above fields Very good expertise in the programming languages Python and C/C++, the numba library, and in applying parallelization techniques using GPU programming (CUDA/OpenCL) and MPI
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and train CNN and SNN models utilizing frameworks such as Keras, PyTorch, and SNNtorch Implement GPU acceleration through CUDA to enable efficient neural network training Apply hardware-aware design
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the integration of both Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs). This position will involve training and optimizing these neural networks using Python frameworks, including CUDA
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needs as well as the ability to work in teams Desirable qualifications Knowledge of German Special knowledge in one of these areas is a plus: HPC (e.g., Workload Scheduler, CUDA, Infiniband) Storage (e.g
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computer science, mathematics or an equivalent with above-average performance You have very good knowledge in one of the following areas: Programming skills in Python, C++ or CUDA Deep learning frameworks
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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