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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies
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must hold a PhD degree or have submitted a PhD thesis. Responsibilities of the Position: Research Conduct world class research in systems security and privacy. Write research articles and publish work in
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computer science/engineering with expertise in a security or privacy research topic At least six years of relevant research experience in computer security, excluding the years spent obtaining a PhD or equivalent
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) Item 03: Proven experience in both programming (Python, R, etc.) and the use of data analysis tools, as well as artificial intelligence / machine learning techniques (punctuation: 22.5) Item 04
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at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems. The PhD researcher will be
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https://www.ntnu.edu/studies/phiv, see Section 6-1 of the PhD regulations for more information. You must have a relevant Master's degree in marine hydrodynamics, aerodynamics, fluid mechanics
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implementation and commissioning Knowledge of machine learning or reinforcement learning applied to control systems is a strong asset Experience with accelerator technology, specifically photocathodes is an asset
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institution and is The Military College of Georgia. More details on the UNG Mission, Values, Vision, and Culture can be found at https://ung.edu/about/mission-vision-values.php Offers of employment
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epidemiology, and AI-accelerated drug and therapeutics discovery. DS/AI-driven Natural, Physical, and Earth Sciences, including physics-informed machine learning, climate and environmental modeling, physics and