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experiences using creative coding, AI-assisted tools, and GPU-accelerated workflows. You have a proven record of producing industry-recognised animation or interactive projects, and you thrive on guiding
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GPU clusters to enhance efficiency and scalability. Knowledge, Skills, and Abilities: Good communication and teamwork skills; Strong skill in large language model customization techniques including
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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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spatial datasets efficiently. Research‑grade software engineering skills (version control, testing, reproducibility, documentation); open‑source contributions are meriting. Experience with GPU/high
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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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://www.rc.ufl.edu/about/hipergator/ ), and the AI NVIDIA GPU SuperPOD (https://news.ufl.edu/2020/07/nvidia-partnership/ ) supporting UF’s campus-wide AI initiative (https://ai.ufl.edu ). These resources are available
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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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, retrieval augmented generation, and in-context learning ● Advanced Statistical Analysis: Proficiency in advanced statistical techniques and probability theory ● GPU Programming: Experience with GPU
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and Memorial Sloan-Kettering Cancer Center, NY. Read more about the project here: https://health.medarbejdere.au.dk/en/display/artikel/supercomputer-and-ai-to-strengthen-danish-cancer-treatment-new