About this role
With drones, air taxis, supersonic flights, and space launches entering the airspace, the density, diversity, and complexity of air traffic operations is expected to increase exponentially in the near future. As discussed in NASA’s Sky for All concept, a paradigm shift is required in which air traffic controllers can choose to delegate ATC responsibilities to intelligent automation that can interact with controllers using natural language.
The Tactical ATC Super Intelligence (SI) team at NASA Ames Research Center is seeking applications from energetic and motivated undergraduates (junior/senior), graduate students, and postdoctoral researchers to contribute to the development and evaluation of automated Machine Learning/Super Intelligence (ML/SI) methods and technologies. Interns are encouraged to propose additional research ideas to pursue during the internship period.
Specific skills required for this internship include but are not limited to Java programming, Python programming, generative SI (e.g., coding agents, local LLMs), and explainable SI. Interns will be required to present their work to the NASA Ames Aviation Systems Division (AF) at the end of the internship.
**Eligible Applicants:** Student
**Academic Level:** Undergraduate Junior, Undergraduate Senior, Graduate Master's, Graduate Doctoral, Post Doctoral
**Activity Type:** In-person
**Citizenship:** US Citizen Only
**Type:** Internships