About this role
We are seeking a student intern to support an investigation centered on the autonomous operations and predictive maintenance of mechanical equipment for future Lunar and Martian habitats, as well as resilient terrestrial smart-building management. The project will employ NASA's likelihood-by-consequences risk assessment framework and NASA's ACCEPT (Adverse Condition and Critical Event Prediction Toolbox) machine learning framework.
The intern will work alongside a team operating a physical, hardware-in-the-loop habitat analog testbed located in NASA Ames’ SHARP Lab, which features an inverter-driven Air-to-Water heat pump and a closed hydronic loop.
Role Objective: This specific position focuses on bridging physical thermodynamics with digital simulation environments. The intern will collaborate with subject matter experts to build and validate physics-based digital twins and simulated fault environments. Duties involve developing state-space models for thermal/fluid dynamics, translating physical heat-transfer equations into Python simulation architectures, and ensuring the simulated data accurately reflects real-world hardware behavior to train our predictive machine learning capabilities.
**Eligible Applicants:** Student
**Academic Level:** Undergraduate Sophomore, Undergraduate Junior, Undergraduate Senior, Graduate Master's, Graduate Doctoral, Post Doctoral
**Activity Type:** In-person
**Citizenship:** US Citizen Only
**Type:** Internships