About the role#
This internship focuses on the safety of runway incursion alerts for aircraft landings. You will investigate how imperfect machine learning perception impacts overall system behavior. The project uses formal specifications to analyze a pipeline consisting of an object detector, a tracker, and an alerting module.
What you'll do#
- Identify semantic conditions that lead to false or missed detections.
- Create temporal and semantic diagnostic specifications to guide system testing.
- Test the detector-tracker-alert pipeline against these specifications.
- Analyze execution logs and violation traces to find recurring failure patterns.
- Determine how perception errors propagate to affect system-level behavior.
- Investigate model-checking methods to characterize potential failures.
What you'll need#
- You are currently an undergraduate senior, a master's student, a doctoral student, or a post-doctoral researcher.
- You have strong programming skills in Python and machine learning packages.
- You understand machine learning, specifically deep neural networks and vision models.
- You have knowledge of formal methods, such as automata theory, formal temporal reasoning, declarative languages, model checking, or SAT/SMT solving.
- Familiarity with computer vision algorithms and aviation systems engineering is a plus.
Location & details#
- Location: Moffett Field, California.
- Term: Summer 2027 (June 7, 2027 to August 13, 2027).
- Work modality: On-site.
- Employment: Full-time internship.
- Citizenship: US citizenship is required.
About NASA - National Aeronautics and Space Administration
The National Aeronautics and Space Administration is a government agency founded in 1958. It conducts research and development in aeronautics, space exploration, and science. The organization operates from various locations across the United States, including its headquarters in Washington, DC. With over 53,000 employees, it manages missions involving rockets, spacecraft, and Earth observation.
How to get in at NASA - National Aeronautics and Space Administration
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