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GPUs). Research Associate: Hold a PhD in high performance computing, computational fluid dynamics or a closely related discipline*, or equivalent research, industrial or commercial experience. Research
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well as access to the group dedicated computing cluster environment with H100, L40s, and A40 GPUs. This post is funded by the UKRI Future Leaders Fellowship, a flexible long-term public funding scheme
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needs, such as assisting the team with evaluating evolutionary algorithms for exploring creative new hand designs, or reinforcement learning for policy optimisation, all within a huge GPU-based simulation
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. First, efficient and scalable training procedure are still needed, irrespective of whether the training is done off-line on a traditional GPU-based architecture, on neuromorphic hardware. Second
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developing and implementing very large deep learning models. Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems