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agentic workflow (Llama, Claude, LangGraph, etc) Experience with training models on GPUs Experience working with Unix and/or Linux, including shell scripting Experience implementing NLP/AI algorithms and
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Workshops (INFOCOM WKSHPS), 2021, pp. 1–6. [4] W. Gao, Q. Hu, Z. Ye, P. Sun, X. Wang, Y. Luo, T. Zhang, and Y. Wen, “Deep learning workload scheduling in gpu datacenters: Taxonomy, challenges and vision
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fonctionnant sur CPU et GPU, cette thèse de doctorat vise à caractériser la dynamique de ces ondes de choc, leur évolution à long terme et leur signature observationnelle. Cette thèse est financée par une bourse
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offers and actions on https://cluster-ia-enact.ai/ . You will work in a rare environment at the intersection of frugal AI, analog computing, reconfigurable electronics and THz imaging. The PhD is directly
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models on GPU infrastructure (SSH access) and distributed computing environments. Strong problem-solving, documentation, and communication skills across technical and non-technical contexts. Ability
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or TensorFlow. Practical background in training and validating models on GPU-based and distributed computing environments. Working knowledge of containerization tools and orchestration platforms (e.g. Docker
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-node GPU training and inference pipelines for foundational models. You'll also develop tools for ingesting, transforming, and integrating large, heterogeneous microscopy image datasets—including writing
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implementing novel and innovative tools, technologies and approaches to fundamental problems in systems and circuit-level neuroscience. For more information about the lab check out: https
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Posting Summary Logo Posting Number RTF00070PO26 USC Market Title Associate Scientist Link to USC Market Title https://uscjobs.sc.edu/titles/156374 Business Title (Internal Title) Associate
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them. Research Computing & AI Enablement - Work with the Architecture team to build scalable HPC and GPU-enabled environments on IaaS cloud sites along with other specialized hosted solutions. Work