Project: The team will design, develop, validate, and demonstrate an integrated analytical capability supporting pattern recognition, anomaly detection, predictive analytics, agent-based modeling (ABM) or equivalent, and decision support in a Ubiquitous Technical Surveillance (UTS) environment. The effort will enhance Joint Force survivability by enhancing the characterization of the UTS threat and providing a mission-agnostic risk-management tool for commanders and operators to utilize across the spectrum of conflict. The enterprise will leverage this analysis and these tools to increase isolated personnel (IP) survivability by enhancing evasion training, planning, and execution, while bolstering force protection for PR task forces.
The Principal Applied Scientist serves as the scientific authority for the development, validation, and application of advanced analytical and simulation models supporting characterization of the Ubiquitous Technical Surveillance (UTS) environment. This individual combines expertise in computational modeling, applied mathematics, physics, and data science to ensure that machine learning models, agent-based simulations, and analytical frameworks accurately represent real-world phenomena and produce scientifically defensible, operationally relevant results.
Working closely with data scientists, machine learning engineers, software developers, and operational subject matter experts, the Principal Applied Scientist is responsible for developing high-fidelity models, validating scientific assumptions, assessing uncertainty, and ensuring that analytical outputs accurately characterize UTS risks and mitigation strategies. This role is instrumental in delivering a transition-ready capability that enables commanders and operators to evaluate operational risk and improve mission survivability.