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, evidenced by e.g. projects on Github. Familiarity with deep learning hardware / accelerators and GPU/CUDA kernels.
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the team You will join the Thermal NDE Research Team within the Department of Computer and Information Sciences. The group hosts state‑of‑the‑art IR cameras, induction coils and GPU‑accelerated
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optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus. Demonstrated research potential is highly desirable
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processing including segmentation. The team is well equipped with high-end workstations with 1Tb RAM and 4090 GPUs, and a 4-8 GPU server for more complex tasks. The University of Warwick is part of
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reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing Knowledge
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on hardware which may include CPUs, GPUs and FPGAs. In particular we are interested in applicants who have experience of modern coding practices and software techniques. The post-holder will work with Prof. Ben
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projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect). The Bourne-Worster group is also well-provisioned with
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) and reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing
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Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing Knowledge of synthetic biology or regulatory sequence design Previous
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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