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resources. Working knowledge of NVIDIA-specific technologies relevant to research computing, such as GPU-enabled workflows, CUDA-enabled tools, GPU resource use, or AI/ML computing environments. Basic
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methods on accelerated or heterogeneous computing platforms, including GPUs, FPGAs or other specialised hardware, for real-time or large-scale physics applications. We welcome candidates whose work is
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REQUIREMENTS The research assistant will be conducting research on GPUs, evaluating scheduling mechanisms to boost GPU utilization. BACKGROUND CHECKS/CLEARANCES Employment with the University will require
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offer A Master’s thesis opportunity (6-12 months, or longer) at the intersection of AI and urban physics. Access to high-performance workstations and GPU resources for training large-scale models
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documentation of HPC architectures, configurations, and operational procedures. Guide the architecture of the next-generation of GPUs through an intuitive and comprehensive grasp of how GPU architecture affects
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research. BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent compute capacity in total across
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trajectory optimization, nonlinear programming, or genetic algorithms. High-performance computing (HPC), parallel numerical workflows, or GPU-accelerated model execution. Terms of Appointment This is a full
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clinical data, high-end GPU resources, and integration into TWIN-X, an EU Horizon Europe consortium with 18 partners from 12 European countries. You will work with data from TUM University Hospital and
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expertise, and substantial GPU and high-performance computing resources. You will be encouraged to contribute ideas, shape new analytical directions and participate in publications, conference presentations
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for government and 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