Machine Learning Applications to Planetary Science Datasets

The NASA Postdoctoral Program (NPP) offers unique research opportunities to highly-talented scientists to engage in ongoing NASA research projects at a NASA Center, NASA Headquarters, or at a NASA-affiliated research institute. 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. This specific opportunity focuses on applying machine learning techniques to planetary science datasets. The researcher will work with mentors at NASA GSFC to apply machine learning techniques to image and spectroscopic data to produce new scientific results and devise new analysis methodologies. Recent advances in machine learning have opened up new frontiers for tackling the 'big data' problem in planetary sciences, with successful applications including feature recognition, semantic segmentation of image data, feature extraction from time series data, and real-time decision making on spacecraft. The future of planetary science involves increasing numbers of missions and vastly larger data rates, requiring a paradigm shift in how planetary science is conducted through advanced computational tools. Results will be published in journals and presented at conferences.