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

Coupled Water-Cycle Retrieval: Linking Precipitation and Soil Moisture Across NASA Microwave Missions

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 5 days ago

); and propagation of physics-traceable soil moisture uncertainty into precipitation estimates. Machine learning approaches are welcome as tools within this framework — for example, learning the space–time

Advancing Multimodal Earth Observation Foundation Models for Wildfire Risk and Vegetation Recovery Assessments

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 5 days ago

-series. Experience exploring machine learning and deep learning techniques for geospatial applications is highly desirable to effectively engage with Earth observation foundation models. Technical

Computational Micromechanics and Microstructure-Sensitive Analysis for Advanced Metallic Materials

National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 5 days ago

the computational work. Researchers in the group have experience with crystal plasticity using finite element and fast Fourier transform methods, fatigue indicator parameters, process modeling and machine learning

Imaging Spectroscopy for Tropical Ecosystem & Biogeochemical Research

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 5 days ago

include advancing foliar trait retrieval algorithms, atmospheric correction over dense humid tropical canopies, machine learning and dimensionality reduction for handling big data, landscape evolution

Advanced Aerosol Data Assimilation of the GEO-LEO Constellation

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 5 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

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

National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | 5 days 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 | 5 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

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

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 5 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