Develop, adapt, and evaluate EO/IR object-detection and separation algorithms; acquire and prepare sensor data; implement reproducible research software in Python; quantify algorithm performance; and transition prototypes for operational use while collaborating with a small multidisciplinary team.

Adapt, integrate, test, and transition a Python-based prototype for detecting closely spaced objects in EO/IR imagery. Connect the prototype to operational message types and systems, harden it for reliability and maintainability, develop automated tests, design clear interfaces, and deploy first in a testbed and ultimately in an operational Kubernetes environment while collaborating with a small multidisciplinary team.