6 algorithm-"INSAIT---The-Institute-for-Computer-Science" Postdoctoral positions at National Aeronautics and Space Administration (NASA)

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

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours 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

Aerosol and Cloud Remote Sensing using Lidar

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 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

Stratosphere and Upper Troposphere Water Vapor Observations by SAGE

National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 3 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

Assimilation of Hyperspectral Infrared Radiance Observations in the GEOS

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 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

Earth Science: frozen hydrometeor remote sensing; ML/AI application to retrieve and track clouds; atmosphere coupling

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 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

A Next Generation Quick Fire Emissions Dataset (QFED)

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 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