14 compressed-sensing Postdoctoral positions at National Aeronautics and Space Administration (NASA)

Integration of remote sensing data and improved physical process representation in NASA modeling systems

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

. Description: The Hydrological Sciences Laboratory at NASA‘s Goddard Space Flight Center is seeking a post-doc candidate to conduct research on the integration of remote sensing data and models to improve

Pre-Fire Burnable Material Assessment and Post-Fire Damage Assessment from Multi-Sensor Remote Sensing

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

and recovery assessment. The effort integrates multi-sensor remote sensing, environmental covariates, and scalable data science workflows. Primary responsibilities are Pre-Fire Burnable Material

Cross-scale thermal remote sensing of biospheric function

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

. Description: Advances in thermal remote sensing are providing new insights into plant water use as well as impacts of heat and drought. Tiered monitoring and measurement approaches using in-situ, drone

Data Science for Satellite Remote Sensing and Earth Science Research

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 days ago

. Description: The post-doctoral fellow will apply machine learning and/or other data science techniques to conduct scientific research, improve remote sensing data products and analysis, integrate machine

New developments in polarimetric ground-based instrumentation for remote sensing and validation of aerosols and clouds

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

Science, Physics, Engineering or similar Expertise with instrument calibration, deployment and data processing Expertise with remote sensing of the atmosphere (aerosols or clouds) Expertise with the use

Remote Sensing from Space: NASA Biodiversity and Ecological Conservation Opportunity with the NASA Earth eXchange (NEX)

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 days ago

innovative research that links in-situ biodiversity observations with NASA remote sensing to generate products and insights that enables NASA stakeholders and partners, including CA-SSN, to quantify

Earth Science: Impacts

National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 1 day ago

information (in situ and remotely-sensed observations as well as climate and weather model output) to enhance decision support across a range of impact sectors and applications (in particular related

Identifying Solar Wind Source Regions Using EUV/FUV Spectroscopy and Multi-Instrument Solar Observations

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

into the solar wind. This property provides a valuable means to connect coronal plasma signatures to in situ solar wind measurements. The project may also involve comparing these remote-sensing observations with

Geologic sources of carbonaceous gasses and their impacts on terrestrial ecology

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 days ago

cadre of satellite and airborne remote sensing platforms, termed ‘plume imagers,’ is demonstrating increasing ability to detect geologic emissions of CH4 and CO2 emissions from space. Unlike ‘area mappers

A Next-Generation Wildfire Risk Assessment System: Integrating Satellite Data, Deep Learning, and Advanced Statistical Analytics

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

field such as Earth Science, Data Science, Computer Science, Remote Sensing, Environmental Science, Statistics, or a related discipline. Technical Skills: Machine Learning & Deep Learning: Demonstrated