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Field
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datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress conditions. Implementing a multimodal approach for large-scale data analysis using CPU and GPU
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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 is also well-provisioned with computational resources and you
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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 is also well-provisioned with computational resources and you
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expertise in key machine & deep learning frameworks and toolsets. Experience in GPU computing, HPC, Containers & Image processing tools would be appreciated. A strong track record of publications in high
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working in interdisciplinary teams Clear record of communicating original results in writing and presentations Desired Qualifications: Knowledge of GPU architecture and experience programming GPUs
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models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi-modality data analysis (e.g., image
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disease insights. The lab has state-of-the-art computing capabilities with an in-house cluster serving 80 CPU cores and 1.5TB of RAM, as well as a newly acquired NVIDIA DGX box with eight H100 GPUs and 224
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determination methods (X-ray crystallography and single-particle cryo-EM) and a high-performance GPU computer cluster for structural biology. Your profile The successful candidate should have: A Ph.D. degree in a
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the Northern 8 cluster, members of Durham University can also submit projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect
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algebra methods targeting large-scale HPC systems. Optimization of linear algebra libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications