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. Desirable criteria Experience working with generative models or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design
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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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or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design Previous collaboration with experimental biologists
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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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Experience in organising and analysing human user trials. B9 Experience with a modern machine learning environment, including use of GPU clusters and modern ML tools and JAX. B10 Experience in working with
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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