8 distributed-algorithms-"Meta" Postdoctoral positions at National Aeronautics and Space Administration (NASA)
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
distribution on a global scale. This project will focus on developing a strategy to best utilize this data in a global atmospheric data assimilation framework. Activities that would be involved in this project
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 3 hours ago
transfer algorithms for NASA GISS‘s general circulation model (GCM) to study radiative interaction and feedbacks between various atmospheric constituents and the climate system. Potential specific topics
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 2 hours ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
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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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 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
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 3 hours ago
analysis is vital tool in understanding how not only where pollutants are emitted, but also how they chemically evolve and distribute throughout the atmosphere and affect both urban and remote regions