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research program; teach and mentor students at the undergraduate and graduate levels; and contribute to the department’s intellectual community and service mission. The positions' start date is July 1, 2027
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Attributes for Success: Bachelor's, master's degree, or PhD in Artificial Intelligence, Machine Learning, or related computing or physics field and up to 2 years of relevant experience, equivalent combination
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days 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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 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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or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning). Documented knowledge of relevant methodologies, both quantitative and/or qualitative, at master’s level
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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hands-on experience to turn your research into practical impact. Profile You are expected to have completed or will complete a Master’s degree in computer science, machine learning, statistics, physics
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating catalytic reaction mechanisms, with a focus