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supporting new research and engineering using ORNL’s Frontier exascale supercomputer for its dense GPU-based HPC resources to train, deploy models and create large-scale production datasets for high-impact
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- and multi-GPU setups, and ability to work with existing codebases to quickly get training pipelines running Deep research interest in one or more of the following areas: 3D Gaussian Splatting, Neural
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for heterogeneousCPU/GPU architectures, with a strong emphasis on performance profiling and optimisation. You will manage defined tasks and milestones and collaborate closely with colleagues across the consortium
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-performance workstations, CPU/GPU clusters, and experimental systems tailored for fish and fly research. This role will necessarily involve both software development and software-hardware integration, with
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/machine learning software development, and even writing software for GPUs or supercomputers. The Person The successful candidate should be able to demonstrate: Currently in the second year of a relevant
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supercomputer for its dense GPU-based HPC resources to deploy models and create large-scale production datasets for high-impact sponsor missions. The candidate will be expected to handle sponsor requirements and
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in high-performance computing systems, storage and I/O. Extensive knowledge on parallel file systems, GPUs, and their trends. (more than 3 years of working with these systems) Experience with
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nearby highways, an indoor SDR testbed for research on next generation wireless communications and sensing, and a GPU Lab for training of advanced machine learning models. IDLab is both part of
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scientists, software and AI engineers, and neuroscientists, you’ll have access to high-performance workstations, CPU/GPU clusters, and experimental systems tailored for fish and fly research. This role will
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/SCI Clearance Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data Statistics, multivariable calculus, and linear