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data from the European XFEL facility at DESY. Project website: https://www.mpinat.mpg.de/628848/SM-Ultrafast-XRay-Diffraction Your profile Eligible candidates have strong skills in computational physics
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software aspects of large-scale AI systems. Areas of interest may include, but are not limited to: • Advanced accelerator chip technologies, such as GPUs or other specialized chips for large-scale AI
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-of-the-Art Infrastructure : Access to advanced sequencing, imaging platforms, and high-performance GPU computing. Research Environment : An international, collaborative, and stimulating research setting at a
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, and interacting with pilots and passengers. Operates and becomes familiar with ground support equipment, such as the aircraft tug, ground power unit (GPU), lavatory service cart, de-icing cart, forklift
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computing (HPC) systems, including GPUs, and programming, such as using CUDA, MPI, AI/ML/DL, and advanced debuggers and performance analyzers. Familiarity with working on open-source projects. About UF
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members in designing and integrating solutions into the AI(X) compute, software and data infrastructure stack, hardening these solutions, testing these on modern high-performance GPU compute clusters, and
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. This project seeks to overcome key workflow and precision limitations in HDR brachytherapy by enabling real-time adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU
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home to HiPerGator, one of the most powerful high-performance computers at a US public university (https://www.rc.ufl.edu/about/hipergator/ ), and recently added the new AI NVIDIA GPU SuperPod (https
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samples. Optimize reconstruction algorithms for efficient large-scale 3D imaging, including high-performance and GPU-accelerated computing where appropriate. Design, optimize, and validate a refractive
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 21 days ago
for the physical characterization of planetary surfaces., in: European Planetary Science Congress. pp. EPSC2024-535. https://doi.org/10.5194/epsc2024-535 Haggstrom, P.L.C. Rodrigues, G. Oudoumanessah, F. Forbes, U