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more than 10,000 CPUs, 60,100 GPU Cores, and over 7,000 Terabytes of storage. Additionally, the number of connected workstations, laptops, and servers totals over 1,000. Windows, Mac, and Linux/UNIX systems
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on them Work on the design, development and operation of GPU and compute cluster systems together with an interactive team Serve as the first point of contact for users for help or problem analysis and
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other data science techniques, with dedicated access to our new GPU server with state-of-the-art compute. A key responsibility will be to help manage, coordinate, and prioritise Hub activities and
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clusters, including CPU and GPU architectures; Proficiency with job schedulers (e.g., Slurm); Knowledge of parallel and distributed computing principles; Understanding of data security and compliance
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multiple languages. Proficient on a computer cluster and ideally programming with GPU nodes. Preferred Competencies Knowledge of relevant scientific fields and procedures. Work both independently and in
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XR facilities including VR/AR headsets, GPU workstations, robotics, 3D immersive wall and 3D motion tracking. For more information about the School please visit our sites at Aeronautical and Automotive
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using a combination of AI, Machine Learning, and other data science techniques, with dedicated access to our new GPU server with state-of-the-art compute. Projects will typically involve implementation
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XR facilities including VR/AR headsets, GPU workstations, robotics, 3D immersive wall and 3D motion tracking. For more information about the School please visit our sites at Aeronautical and Automotive
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small cluster computers, high-end GPU nodes and specially configured workstations on which experiments are conducted. You will be working in a team of junior and senior system administrators. Naturally
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-of-core techniques, GPU algorithms and architecture. Work duties As an associate senior lecturer, you will have the chance to apply a long-term focus on the challenging research questions you are passionate