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                Employer- Forschungszentrum Jülich
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                resources, including 200+ NVIDIA A100 GPUs and group workstations. Image quality will be assessed using quantitative metrics and clinical expert qualitative review. Privacy safeguards will be built 
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                , and supportive atmosphere, equipped with state-of-the-art research facilities, including dedicated GPU clusters, data servers, and personal GPU-enabled workstations. You will join a multidisciplinary 
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                /GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key 
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                suitable for part-time employment. Starting date: 17.10.2025 Job description: Design, develop and apply an flexible and integrative multiscale FWI using GPU-accelerated spectral-element simulations (Salvus 
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                applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience with ML/DL workflows and 
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                IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 21 days agointernational projects, · collaboration with application developers and domain experts on highly scalable parallel applications with focus on: - development and implementation of parallel aplications, - GPU 
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                secretion systems (T4SS). The laboratory provides all the equipment required for the project, including standard microbiology facilities (L1 and L2) and biochemistry equipment (AKTA pure), GPU computing 
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                optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus. Demonstrated research potential is highly desirable 
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                in rivers or estuaries with applications to plastic transport. The transport models will be included in existing shallow-water solvers running in hybrid CPU-GPU architectures. The expected workplan 
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                , as is experience with scientific, numerical, and/or GPU programming; • Have some prior experience with data science and/or machine learning; • Hold values such as honesty, modesty, collectivism