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Field
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research computing and visualization services. ARC systems currently host 50,000+ CPU cores, 500+ advanced GPUs, and 10+ petabytes of storage. We stay abreast of novel and developing trends in research
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on hardware which may include CPUs, GPUs and FPGAs. In particular we are interested in applicants who have experience of modern coding practices and software techniques. The post-holder will work with Prof. Ben
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on heterogeneous processor types Optimized GPU computing and exploitation of GPU architectures for HPEC (tensors, multi-GPU instantiations, advances in GPU for AI/ML) Compute-focused optimization of System-on-Chip
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, combining scientific excellence with real-world impact. They operate within a unique ecosystem that includes the AI Foundry (state-of-the-art GPUs and engineering capacity), the System for User Knowledge (SUK
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artificielle (IA) (CPU, GPU, accélérateurs d'IA, etc.) nécessitent une puissance élevée et des réseaux de distribution d'énergie (PDN) optimisés pour améliorer l'efficacité en puissance et préserver son
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Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network. This is partly
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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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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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, implementing efficient monitoring of the various deployments using Grafana and Prometheus and the autoscaling of compute nodes for CPU and GPU workloads across various cloud providers. Key responsibilities will
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learning frameworks such as PyTorch, JAX, or TensorFlow. Experience with C++ and GPU programming. A strong growth mindset, attention to scientific rigor, and the ability to thrive in an interdisciplinary