7 machine-learning-phd Postdoctoral positions at National Aeronautics and Space Administration (NASA)

Machine Learning Applications in Solar System Exploration

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago

and related activities. Strong programming skills are a must, including experience with machine learning. Good written and oral communication skills in English are important. Point of Contact Mikeala

Advanced Aerosol Data Assimilation of the GEO-LEO Constellation

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 8 days ago

to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning

Assimilation of Hyperspectral Infrared Radiance Observations in the GEOS

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 9 days 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

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 6 hours 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

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

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 7 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

A Next Generation Quick Fire Emissions Dataset (QFED)

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 8 days 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

Strengthening NASA Air Quality Observations with Low-Cost Sensor Data

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 8 days 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