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vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D projects Key Competencies Able to build and maintain strong working relationships with
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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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/10.1021/jacs.4c01897 ). The new Fortran implementations will further be ported to GPU, either by you (if you are interested in this) or by our collaborators at the CSC supercomputing center. For position 2
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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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developments; Significant experience with the development of custom modules using GPU-accelerated APIs for deep learning (e.g., Pytorch); and Publications in top-tier venues in Machine Learning and/or Signal
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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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to support model-based control of Deep Brain Stimulation (DBS) and personalised treatment strategies for Parkinson's disease. Develop and optimise scalable data processing pipelines, including GPU acceleration
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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