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Field
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Generative AI (GenAI) applications, including GPU-hosted LLMs, containerized workloads, and internal agent platforms. Manage Model Context Protocol (MCP) servers, ensuring context routing, memory persistence
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data processing, as well as experience working with large biological datasets in GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
. The postdoctoral scholar will be expected to improve on existing GPU-accelerated ocean models and develop laboratory experiments (in the Joint Fluids Lab at UNC), analyze results, publish in peer-reviewed journals
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse
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astrophysical free boundaries. Responsibilities include running high-resolution GPU-accelerated simulations on exascale computing systems, developing and applying geometric measure theory tools to quantify
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. Experience with GPUs and performance optimization of ML at scale. Familiarity with containerization and HPC workflows. Notes: This is a full-time, career appointment, exempt (monthly paid) from overtime pay
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modeling, or ordinary/stochastic differential equations. Experience in computational, statistical, or machine learning method development in any discipline. Experience in GPU computing frameworks (e.g
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service deployments, or publications in AI/science venues. Experience with GPUs and performance optimization of ML at scale. Familiarity with containerization and HPC workflows. For full consideration
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Engineer will support the development and operation of the GPU-accelerated, real-time data analysis pipelines that will turn images from the world’s largest digital camera into discoveries. Three years
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3T Siemens MR scanners, OPM-MEG, EEG, eye tracking, and TMS laboratories. They will also have access to Princeton's world-class computational infrastructure, including GPU systems capable of running