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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 30 days ago
imaging, and structured electronic health record (EHR) data. The postdoctoral researcher will work closely with the Director for Cardiovascular Artificial Intelligence Research and contribute to the design
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/ Machine Learning Artificial Intelligence, Machine Learning and Autonomy Appl Deadline: 2026/06/17 11:59PM (posted 2025/06/17) Position Description: Apply Position Description The Skinnider Lab
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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Ferreira Zandoná (College of Dentistry) at The Ohio State University. This position offers a unique opportunity to lead cutting-edge research at the intersection of artificial intelligence and dental health
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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seeking a postdoctoral appointee to join our team focused on designing the communication infrastructure for next-generation High-Performance Computing (HPC) and Artificial Intelligence (AI) systems
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starting July 2025, and will remain open until excellent fits are found. The successful candidate will develop and apply computational approaches to chemical datasets, with artificial intelligence/machine
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starting July 2025, and will remain open until excellent fits are found. The successful candidate will develop and apply computational approaches to chemical datasets, with artificial intelligence/machine