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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in
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high intellectual merit and the willingness to use machine learning and/or AI techniques. Essential Duties and Responsibilities: Successful candidates are expected to develop an impactful research
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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to student learning, research, health care, and service is seeking applicants for a postdoctoral fellow position in the Department of Pediatrics, Division of Medical Genetics. The candidate will join a dynamic
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the areas: AI, deep neural networks, machine learning, applied topology, probability, statistics, signal processing. About the School The School has an exceptionally strong research presence across
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to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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simulation methods, decision theory, uncertainty quantification, machine learning. Applications and areas of key innovation Image analysis, computer graphics, autonomous and assisted driving, 3D scene analysis
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to work standing at bench, seated at biosafety cabinets, or in front of a microscope for extended periods while performing scientific experiments. Ability to work in front of a computer for extended periods
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
, designing natural language interfaces for more intuitive navigation of the BDC environment, creating BDC-specific foundation models, and enabling large language models (LLM) and machine learning-based