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molecular dynamics simulations and was specially designed for parallelisation on GPUs. It is open source and licensed under the LGPL. Details can be found on the website https://halmd.org Job-Description
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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 model generation, point cloud rendering, visual effects (GPU shader, shadergraph, VFX) and 3D scene design Development of AR/VR applications What you bring to the table Full-time student at a German
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programme of computer science, mathematics, physics, electrical engineering, computational linguistics, or similar with good grades PyTorch skills: experience in training machine learning models with one
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therapies, cell programming and repair, bioengineering, and computational health. Through this research, we build the foundations for medical innovation. Together with our partners, we seek to accelerate
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-unterstütze Simulation« team offers you exactly that. What you will do Optimizing existing code for electronics application considering multi-CPU and multi-GPU usage (implementation in jax and/or numpy and/or C
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benchmark them with a realistic case study. The main focus of the project can develop either more in the mathematical theory of MCMC, the implementation of code for the Jülich supercomputers (GPU/CPU
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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
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic
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., based on the 1D or analytical model) Hybrid simulation approach (e.g., which combine CFD and 1D simulations) High Performance Computing and/or GPU programming for this domain Machine learning algorithms