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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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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
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6G testbeds (indoor and outdoor) with GPU clusters and edge computing platforms Global Internet measurement infrastructure and satellite network access Opportunities to engage with Internet
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technological platforms on site. The PhD student's work will be carried out at the IGBMC's integrative biology center. He/she will have privileged access to the team's computing server (GPU node) and the