44 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" Postdoctoral positions at National Aeronautics and Space Administration (NASA)
Sort by
Refine Your Search
-
National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 month ago
improve estimation of rates of snow accumulation, snowmelt, ice melt, and sublimation from snow and ice worldwide at scales driven by topographic variability. We seek projects focusing on the use of machine
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 month ago
New Year's fires. Geophysical Research Letters, 49, e2021GL096270. https://doi.org/10.1029/2021GL096270 Millán, L., Read, W. G., Santee, M. L., Lambert, A., Manney, G. L., Neu, J. L., et al. (2024
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month 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
-
National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 7 hours ago
accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Questions about this
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 7 hours ago
to approximate expensive forward and adjoint simulations while preserving underlying physics. Uncertainty-aware inference: combining physics-informed learning for regularization with probabilistic generative
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month 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
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
carbon-cycle modeling. The project will build a unified modeling framework that uses GEDI LiDAR and Landsat/HLS data to train deep learning models capable of predicting forest structure variables such as
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 month ago
(2018); https://doi.org/10.1063/1.5033338 Shuyan Zhang, Alexander Soibel, Sam A. Keo, Daniel Wilson, Sir. B. Rafol, David Z. Ting, Alan She, Sarath D. Gunapala, and Federico Capasso, “Solid-immersion
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 7 hours ago
Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent
-
National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 9 minutes ago
Designated 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