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the complexities of the human regulome through advanced cell-free DNA profiling and developing cutting-edge computational algorithms and molecular profiling techniques. Our research focuses on early cancer detection
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA
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external) provides algorithmic and data-driven solutions providing fairer access to public educational resources. The lab enables school districts to optimize large-scale equitable resource allocation
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unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
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our team. We are looking for postdoc candidates to develop and apply cutting-edge technologies in spatial transcriptomics, single-cell sequencing, machine learning, and functional genomics
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Detection: Develop and implement algorithms for identifying oscillations in the grid and extracting important oscillation modes (frequency, damping, etc.). System Strength Analysis: Use system metrics like
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with a highly competitive salary. Essential Duties and Responsibilities: Conduct research and develop novel AI/ML algorithms and solutions. Disseminate research findings in publications, posters, project
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g
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a 3-year DOE-sponsored project that started in September 2024. The Postdoctoral Research Associate working on P1 will develop and test deep learning algorithms for model emulation and model parameter