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infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi-node GPU training and inference pipelines for foundational models. You'll also
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numbers effects beyond what is currently possible. • Perform mathematical and numerical analysis of tensor network methods. • Work on GPU implementation of tensor network solvers. • Disseminate research
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, TensorFlow) with several years of practice Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning
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GPU clusters for large-scale analyses. Terms of employment The average weekly working hours are 37 hours per week. The position is a fixed-term position limited to a period of 3 years. The employment is
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feedback; optimize for real-time performance; distribute computations between GPU and device-proximal processors; ensure precise synchronization with visual and auditory stimuli. Real-Time Collision and
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supportive team environment that promotes collaboration and knowledge sharing. Access to world-class computational infrastructure, GPU-based computing environments, and unique high-quality cryoET datasets
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projects Preferred: Experience with educational technology development and web programming LAMP stack design and implementation experience Knowledge of GPU and FPGA cluster management Experience with federal
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Posting Summary Logo Posting Number RTF00122PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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Posting Summary Logo Posting Number RTF00122PO26 USC Market Title Post Doctoral Fellow Link to USC Market Title https://uscjobs.sc.edu/titles/156387 Business Title (Internal Title) Post Doctoral
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https://gen3.org/, https