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Field
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between INRIA and LJLL which focuses on high performance scientific computing. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7598-PIETOU-006/Candidater.aspx Requirements Research
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software aspects of large-scale AI systems. Areas of interest may include, but are not limited to: • Advanced accelerator chip technologies, such as GPUs or other specialized chips for large-scale AI
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capabilities. We can access a high-performance computer cluster with the most advanced GPU resources. We also partner with the New York Proton Center, which houses one cyclotron, three rotational gantry
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Engineers. Serve as liaison with Princeton Research Computing staff on GPU cluster related issues. Professional Development Learn the underlying science, mathematics, statistics, data analysis, and algorithms
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development. You’ll have access to state-of-the-art high-performance computing infrastructure and GPU clusters essential for conducting cutting-edge AI, software engineering, and security research. Salary range
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and clinical MR systems fully dedicated to research, state-of-the-art local and scalable cloud-based compute infrastructure (CPU, GPU) and workshops for mechanical, electrical and electronic development
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significant computational component in deploying multi-GPU codes to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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, production-grade pipeline encompassing scalable video preprocessing, model training, and inference workflows. Implement GPU-accelerated training and inference, standardized evaluation protocols, and
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approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms