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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
of Computer Science at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
of Computer Science at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is
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evaluation of alloys; familiarity with finite element methods. Skills and experience in programming, machine learning, or signal processing are all considered a plus. Outstanding UA benefits include health
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in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other
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machine learning and neuromorphic hardware is to utilise material platforms that exhibit multiwell behaviour. One challenge here is to understand and control the dynamic response of the system for complex
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for this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be potential
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that interaction represents the foundation of active learning and fosters acquisition and retention of knowledge, as opposed to passive reception in traditional teaching. Some benefits of MR are now well established
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and as part of a collaborative, interdisciplinary team. Commitment to publishing research and pursuing a career in academic or translational research. Experience with statistical modeling, machine
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a