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machine learning pipelines, with GPU-accelerated environments tailored to foundation model training, data harmonization, and predictive analytics. The Center is embedded within the UC Davis ecosystem, with
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resources of 48 GPUs, including 16 * NVIDIA A30, 16 * NVIDIA A40, and 16 * NVIDIA A100. Detailed information about the CEEC Department can be found at: http://www.unlv.edu/ceec MINIMUM QUALIFICATIONS
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. Experience with graph-based data analysis or anomaly detection methods. Exposure to high-performance or GPU-based computing environments. Demonstrated ability to contribute to publications or technical reports
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tracking), dataset curation, HPC/GPU programming, blockchain for secure data, C-family languages, and embodied AI/robotics are a plus. Experience with general network resilience, cellular automata
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, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data processing or willingness to learn quickly. Publications, thesis work, or demonstrable
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). Experience with distributed systems, GPU computing, or cloud-based simulation environments. Knowledge of human-in-the-loop simulation, training effectiveness evaluation, or synthetic environments. Experience
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours 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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(Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities through the CASS network. NYUAD also has guaranteed observing time on the Green Bank
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the College of Engineering. UNLV GPU Cluster (named RebelX) is also available for A.I. research and education. Detailed information about the CEEC Department can be found at: http://www.unlv.edu/ceec MINIMUM
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of the Empire AI Consortium, researchers have access to state-of-the-art computational infrastructure, including large-scale GPU clusters and high-performance computing resources. The Institute has