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

A Next-Generation Wildfire Risk Assessment System: Integrating Satellite Data with Deep Learning Insights

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

wildland-urban interfaces— across a wide range of climate conditions. Using machine learning methods, we will optimize the weightings of each contributing factor and identify the key drivers of wildfire risk

Data Science for Satellite Remote Sensing and Earth Science Research

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

A Next-Generation Wildfire Risk Assessment System: Integrating Satellite Data with Deep Learning Insights

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 months ago

wildland-urban interfaces— across a wide range of climate conditions. Using machine learning methods, we will optimize the weightings of each contributing factor and identify the key drivers of wildfire risk

Exobiology: Living Systems Science

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 3 months ago

machine-learning applications for astrobiology. Areas of investigation include: - Living systems detection and characterization - Mars sample return science and tools. - Standards of evidence in life

Data Science for Satellite Remote Sensing and Earth Science Research

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

CLARREO Pathfinder Science

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

intercalibration studies, and enhancing and advancing intercalibration algorithm approaches and hyperspectral analysis with machine learning. We are also interested in studies to evaluate decadal time-variant

Remote sensing applications for mapping and monitoring global forest carbon stock and dynamics

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 3 months ago

research using various statistical and machine learning approaches to develop regional and global products and improve our understanding of the drivers of carbon stock changes across a variety of ecosystems