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atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address fundamental scientific challenges, including global cloud
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
collaborate with colleagues from multiple universities across the Research Triangle, the United States, and even the world. Position Summary The Research Assistant (RA) will support advanced research in
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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in artificial intelligence (AI) for settings involving multiple interacting decision-makers---whether autonomous AI agents, humans, or a combination of both. Applications include mixed-autonomy
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POSTDOCTORAL COMPUTATIONAL BIOLOGIST FELLOW, under the Collins Genomics Lab to lead pioneering studies of genetic risk for cancer based on large-scale genome sequencing datasets towards the ultimate goal
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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with Neutrons. Jason Fry’s group has worked on significant contributions to Nab and BL3 and supports their experimental efforts through work from the PI and undergraduate students through multiple NSF
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data management sufficient to create, transform and integrate data in a variety of resolutions and formats. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and