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decays and related physics object performance studies , development of the real-time analysis (RTA) in particular with ML/AI reconstruction on hybrid GPU/FPGA architecture for the electromagnetic
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application workflows across CPU/GPU clusters, parallel storage, and hybrid cloud platforms. Responsibilities include configuring and optimizing large-scale Linux environments, implementing job scheduling and
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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Specific Integrated Circuits (ASIC), Processors (CPU, GPU, VPU and accelerators), Field Programmable Gate Arrays (FPGA) and System-on-Chips (SoCs), as well as Intellectual Property (IP) Core developments for
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part of the core PLI team, which includes top-tier faculty, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300
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package, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https
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intelligence models (LLMs) in multi-GPU environments. Preparation of technical documentation, best practices for development and operation. Where to apply Website https://sede.uvigo.gal/public/catalog-detail
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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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scenarios Convolutional neural networks for computer vision require substantial computing resources and introduce significant latencies even in modern GPU systems. This project investigates neuromorphic
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at the IRIT-ENSEEIHT campus in Toulouse. Integrated within the REVA team at IRIT. Strong interaction with ALICIA-Vision LabCom partners (CNRS / Technicolor-Mikros). Where to apply Website https://emploi.cnrs.fr