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. We train open foundation models with hundreds of billions of parameters on thousands of GPUs on one of the largest AI-ready supercomputers in Europe. The team counts more than a dozen full-time
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have access to substantial AI compute, including in-house state-of-the-art H200 GPU servers, alongside further capacity through the Norwich Data Centre and access to national-scale AI compute through
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to substantial in-house H200 GPU infrastructure, further capacity through the Norwich Data Centre and routes to national-scale AI compute such as Isambard-AI. Collaboration with the Earlham Biofoundry will provide
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into robust, maintainable analysis tools and pipelines Implement and optimize large-scale deep learning workflows on GPU-enabled High-Performance Computing (HPC) environments Prototype using emerging computer
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the group, translating cutting-edge deep learning algorithms into robust, maintainable analysis tools and pipelines Implement and optimize large-scale deep learning workflows on GPU-enabled High-Performance
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baselines Solid Linux experience in production environments (RHEL/Almalinux/Ubuntu) Hands-on HPC background: Slurm, parallel file systems (Weka, Lustre, Ceph), GPU workloads and high-speed networks
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practices and international standards.Leverage VIB Data Core services, including high-performance computing pipelines and large-scale GPU resources, to scale ML development and deployment. Your profile PhD
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commercial sponsors. A particular strength is real-time RF system development leveraging in-house FPGA, GPU, and SDR platforms. Importantly, SDD has successfully transitioned multiple capabilities for real
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the thermal process from GPU computation to radiative cooling Integrate the algorithms into a larger computational satellite simulation environment Identify new cyber-physical systems research topics related
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to gather requirements, manage expectations, and balance competing priorities. Experience supporting high-performance or GPU-enabled scientific computing environments, including NVIDIA/CUDA, performance