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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 9 hours ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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scheduled. Reliable attendance for required meetings/workshops and scheduled research team meetings. Interest in U.S. history and/or criminal justice; willingness to learn archival workflows and ethical
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Military Research Institute (PMRI) plays a pivotal role in expanding the reach and impact of PMRI across all branches of the U.S. military, while fostering strategic partnerships and supporting the academic
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of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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that are facile with computationally efficient, rigorous machine learning for image region identification, demonstrate an understanding of both planetary and scalable computer science, and have publication
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Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible for an Exchange Visitor
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Intelligence (AI), Machine Learning (ML), and data-driven decision support systems for precision agriculture. The Assistant Professor – AI & Data-Driven Precision Agriculture position is part of a strategic
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enterprise and leadership in key academic areas. Learn more at https://www.uta.edu/administration/president/strategic-plan/rise100 . This is an exciting time to join UTA and contribute to its bold vision
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off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC Requirement
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 9 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward