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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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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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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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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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skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, while working with the world’s fastest computers
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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 | about 18 hours 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