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approaches for important questions in neuroscience. We have multiple current and incoming NIH projects to establish cellular cell type architecture maps of mammalian brains using mice as an animal model. Three
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algorithm development; · THz transceivers for high-frequency communication channel measurement and sensing; · Real-Time Digital Simulator (RTDS) and Solar & Wind Emulator for real-time
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: Employing satellite observation and machine leaning to improve model representation of ice sheet surface melt”. The candidate will work under the direction of Prof Nowicki and in collaboration with multiple
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within tissues using our in-house developed spatial transcriptomics-based technology (Spatial VDJ). Using established and newly developed algorithms, we map B cell evolution within tissues, including class
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to seek an optimal integration between the physical representations of the various processes and the computing power of the AI algorithms. Key duties Develop a robust framework to simulate streamflow
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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data pipelines Comply with data security guidelines Data analysis (25%) Data reduction of predictor and outcome measures Determine and implement optimal strategies for testing multiple hypotheses Utilize
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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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development as well as field data collection at multiple test sites in Ethiopia. Job assignments The successful candidate will join a large, collaborative team of researchers with expertise in electromagnetic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
meteorology, and numerical modeling techniques with an understanding of local-scale physical and chemical processes from multiple emissions sources as represented in current models, and quantitative analysis