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Field
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container technologies in HPC environments. Experience with multiple system deployment mechanisms (Warewulf, PXEboot, Cobbler, Bright). Experience with GPU clusters (NVIDIA, AMD) for AI/ML and scientific
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utilizing GPU (NVIDIA and AMD) clusters for AI/ML and/or image processing. Knowledge of networking fundamentals including TCP/IP, traffic analysis, common protocols, and network diagnostics. Experience with
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rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels. This role offers a unique opportunity to
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, workflow orchestration, and high-throughput data processing, as well as experience working with large biological datasets in GPU-based computing environments. What we provide: A competitive compensation
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frameworks (e.g., PyTorch). Engineering skills: GPU/cluster training, experiment tracking, data engineering. Ability to formulate research questions, run empirical studies at scale. *for students with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
Engineer will support the development and operation of the GPU-accelerated, real-time data analysis pipelines that will turn images from the world’s largest digital camera into discoveries. Three years
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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and high flexibility in where and when you work. Access to HPC resources (including GPU clusters) at Helmholtz, the Leibniz Supercomputing Centre (LRZ), and the Forschungszentrum Jülich (FZJ). Training
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, mathematical sciences, or applied mathematics/engineering, and who are motivated to engage in AI research in earnest. We also welcome applicants with the following experience: - Operation and use of GPU-based