46 algorithm-"Multiple"-"University-of-Cambridge" Postdoctoral positions in United States
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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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on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems
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Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and analysis of large-scale 2D/3D scientific data
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Requisition Id 15448 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large
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scale and resolution. This ambitious project spans multiple institutes including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute, bringing
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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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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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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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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
supporting multiple probes simultaneously. Swarms also provide the usual benefits of multi-element array reception, namely robustness to single point failures and transmit/receive diversity. The downside
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of application development techniques (numerical methods, solution algorithms, programming models, and software) at scale (large processor/node counts). A record of productive and creative research as proven by