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Field
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algorithms to improve methods for peptide identification from raw mass spectral data. The use of orthogonal information such as multi-enzyme digestions, to verify the presence of a peptide using different
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collection, and data analysis. Work activities may include the following. • Developing analysis tools to extract physical meaning from in-situ process data. • Developing machine learning algorithms to drive
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/Augmented Reality, Software Engineering, Database Systems, Algorithms, Artificial Intelligence. In addition to teaching, the position requires weekly office hours, attending faculty meetings, participation in
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on the design, development, and realization of future communications technologies. You will be part of the team and contribute to ongoing developments in theory, algorithms and translation to practice in
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for fully automated analysis of nuclear cardiology data using novel algorithms and machine learning techniques, and on the development of integrated motion-corrected analysis of positron emission tomography
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, computer science, or other related fields. The candidates who have experience in electronic system design (e.g., PCB design, integrated circuit design, packaging, and fabrication) or algorithm development
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists of 12 awardees across the US with whom UNC is partnering to implement data collection and analysis
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at least one component substantively uses and/or develops artificial intelligence tools, including but not limited to machine learning, deep learning, neural networks, computer vision, or genetic algorithms
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment