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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
Engineering stresses the application of science and engineering, mathematical analysis, and computer techniques to biomedical problems. The research and entrepreneurship of the faculty, students, and staff aim
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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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
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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
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visualizations, manuscripts, and conference presentations for dissemination of project results. Required Qualifications PhD in plant biology, genetics, genomics, bioinformatics, computational biology, or related
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and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning
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Computer Science, Electrical Engineering, Computer Engineering, or a related field. Preferred Qualifications Strong publication record in top-tier AI conferences or journals.. Strong written and oral
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/biomechanical analysis, computer vision approaches to pose tracking from video, surface electromyography (EMG) recording and analysis, vocal recording and analysis, dataset preparation, time-series analysis
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, who are interested in advancing management strategies and disease prevention and control in dairy cattle populations. Applicants with expertise in complementary disciplines (e.g., computer vision, AI
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enzyme activities and conduct directed evolution, structure-guided protein engineering, and machine learning-guided protein engineering studies to improve enzyme and pathway function. The ability