Physical and AI Satellite Remote Sensing Algorithm-development

Organization

National Aeronautics and Space Administration (NASA)

0048-NPP-NOV
26-LRC-Earth Sci

November 1, 2026 6:00:59 PM Eastern Time Zone

The NASA Postdoctoral Program (NPP) offers unique research opportunities for highly-talented scientists to participate in ongoing NASA research projects at a NASA Center, NASA Headquarters, or a NASA-affiliated research institute. Fellowships last one to three years, are competitive, and aim to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology.

The Principal Component-based Radiative Transfer Model (PCRTM) group at NASA Langley Research Center has developed innovative radiative transfer models and associated retrieval algorithms for satellite remote sensing applications. PCRTM has been implemented for thermal instruments including NAST‑I, S‑HIS, AIRS, CrIS, IASI, and CLARREO, as well as for solar instruments such as CPF, SCIAMACHY, EMIT, OMPS, and OMI/TEMPO O3. The PCRTM calculates radiance/reflectance spectra across multiple spectral regions, from ultraviolet to microwave, and its retrieval algorithms are used operationally to produce weather and climate products from instruments aboard Suomi NPP, NOAA‑20, and NOAA‑21.

• AI‑Enhanced Radiative Transfer Modeling:
  Improve computational speed of the PCRTM with advanced AI techniques while maintaining accurate Jacobians.
• AI‑Based Retrieval Algorithm Development:
  Build next‑generation AI‑based retrieval algorithms that incorporate spatial and temporal information and real satellite data.
• Novel Applications of PCRTM Retrieval Products:
  Leverage existing PCRTM products and real satellite data to create new products such as 3‑D atmospheric wind vectors, wildland fire prediction, surface change characterization, AI algorithms for weather prediction, and planetary boundary layer characterization.

Earth Science

• Xu Liu – xu.liu-1 –

• PhD in physical science (e.g., atmospheric science, physics, computer science).
• Experience analyzing satellite and geospatial data.
• Skills in AI, machine learning, deep learning, Keras, and PyTorch.
• Proven track record of scientific publications and collaboration.

• Citizenship: U.S. citizen or lawful permanent resident.
• Degree:
  Doctoral degree.

Questions about this opportunity? Please email npp.