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

Characterization of ionospheric dynamics through application of machine learning techniques to GPS measurements

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 2 months ago

Organization National Aeronautics and Space Administration (NASA) Reference Code 0202-NPP-MAR26-JPL-HelioSci How to Apply All applications must be submitted in Zintellect Please visit the NASA Postdoctoral Program website for application instructions and requirements: How to Apply | NASA...

Advanced Aerosol Data Assimilation of the GEO-LEO Constellation

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour 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

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

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

A Next Generation Quick Fire Emissions Dataset (QFED)

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour 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 | about 1 hour 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

Advanced Aerosol Data Assimilation of the GEO-LEO Constellation

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months 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

Aerosol and Cloud Remote Sensing using Lidar

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months 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

A Next Generation Quick Fire Emissions Dataset (QFED)

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months 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

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

National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | 2 months 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

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

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months 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