The future of planetary science requires a paradigm shift in how planetary science is conducted, with increasing numbers of missions, instruments that produce vastly larger data rates and volumes, resulting in much larger amounts of data being recorded for analysis, and NASA is looking to solve this 'big data' problem in planetary sciences using advanced computational tools and machine learning techniques.
Requirements
- Experience in machine learning applications in the geosciences or astronomy
- Significant experience in computational techniques applied to scientific problems
- Strong computer coding skills
- Experience with python-based neural net architectures such as PyTorch, TensorFlow and Keras
- Machine learning techniques
- Advanced computational tools
- Python programming language
Responsibilities
- Apply machine learning techniques to image and spectroscopic data to produce new scientific results
- Devising new analysis methodologies
- Conduct data analysis by detailed inspection, calibration, cataloging and modeling of every byte of data
- Make rapid analysis of very large datasets tractable
- Feature recognition and semantic segmentation of image data
- Feature extraction from time series data from plasma and field detection instruments
- Real-time decision making on spacecraft
Other
- Degree: Doctoral Degree
- U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible for an Exchange Visitor J-1 visa status; and, Applicants for LPR, asylees, or refugees in the U.S. at the time of application with 1) a valid EAD card and 2) I-485 or I-589 forms in pending status
- Applications with citizens from Designated Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States
- A complete application to the NASA Postdoctoral Program includes: Research proposal, Three letters of recommendation, Official doctoral transcript documents
