35 data-science Postdoctoral positions at National Aeronautics and Space Administration (NASA) in UNITED-STATES

Studying Biosphere Drivers, Change, and Impacts in Terrestrial and Coastal Ecosystems Using Remote Sensing Data and Modeling

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 7 hours ago

Biospheric modeling to address critical science and applications: 1.Developing innovative new methods to integrate remote sensing, custom products and other observations with process models leveraging data

Airborne Lidar Measurements of Atmospheric Trace Gases, Aerosols, and Clouds

National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 7 hours ago

. These one- to three-year fellowships are competitive and are designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology

ICAR - Advancing Multi-Messenger Biosignature Techniques with Machine Learning

National Aeronautics and Space Administration (NASA) | United States | about 13 hours ago

of focus in this project, including analytic techniques, data science, machine learning, and biosignature science. Field of Science: Astrobiology Advisors: Caleb Scharf caleb.a.scharf@nasa.gov 650.346.3760

Advancing Terrestrial Ecology, Wildfire Fuel Monitoring, or Agricultural Applications, or Associated Activities through VSWIR Imaging Spectroscopy

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 7 hours ago

missions (e.g., Surface Biology and Geology - SBG). This could involve advancing atmospheric correction, dimensionality reduction, or machine learning approaches for handling big data in order to improve

Predicting Precipitation-Driven Disruptions to Critical Infrastructure

National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 13 hours ago

. Candidates must possess an exceptional background demonstrating expertise across atmospheric physics, computational modeling, and data science. Knowledge of atmospheric science or meteorology, and computer science

Physical and AI Based Satellite Remote Sensing Algorithm-development and Applications

National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | about 13 hours ago

atmospheric science, physics, and computer science. Experience in analyzing satellite data and geospatial data are desired. Skills in AI, machine learning, deep learning, keras, Pytorch are preferred. A proven

Machine Learning Applications in Solar System Exploration

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 13 hours ago

, computer science or physical or biological sciences with experience in training and evaluation of AI systems. This may include development of robotic systems, training of neural nets for data assimilation

Determining Main Belt and NEO Origins and Increasing Reliability of Asteroid Detections

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 7 hours ago

well as useful information about the targets of the Near-Earth Objects Surveyor (NEOS) mission, which will launch in late 2027, feeding into reliability analyses for its asteroid detections. Field of Science

Reducing greenhouse gas retrieval biases by improving aerosol representation

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 13 hours ago

. These one- to three-year fellowships are competitive and are designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology

Next-generation wildfire risk assessment using deep learning based high resolution fuel maps and stochastic fire spread modeling

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 13 hours ago

should have a strong background in data science, machine learning, remote sensing, wildfire science, or a related field. Experience with deep learning frameworks, satellite observations (e.g., Sentinel