17 learning Postdoctoral positions at National Aeronautics and Space Administration (NASA)

Advancing Terrestrial Ecology, Wildfire Fuel Monitoring, or Agricultural Applications, or Associated Activities through VSWIR Imaging Spectroscopy

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 hour ago

missions (e.g., Surface Biology and Geology - SBG). This could involve advancing atmospheric correction, dimensionality reduction, or machine learning approaches for handling big data in order to improve

A Next Generation Quick Fire Emissions Dataset (QFED)

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

Data Assimilation of Combined Lidar and Polarimeter Observations for the AOS Mission

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 30 days 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

Remote sensing of snow parameters in support of Surface Biology and Geology (SBG) mission

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 month ago

learning tools to do snow parameters retrievals. Current projects in our lab range from theoretical and experimental atmospheric science into radiative transfer, climate dynamics, remote sensing of the land

Assimilation of Hyperspectral Infrared Radiance Observations in the GEOS

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

Opportunities in Remote Sensing, Modeling, and AI/ML with NASA SPoRT

National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | about 1 month ago

to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding

Strengthening NASA Air Quality Observations with Low-Cost Sensor Data

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 1 month ago

analysis software packages. Demonstrated success in collaborative environments. Experience with one or several of the following: machine learning, data assimilation, ArcGIS, NASA satellite datasets. Point