Senior Air-to-Air Modeling and Simulation Analyst Date Posted:

1 October 2026

Closing Date:

October 31, 2026

Recruiter:

Johns Hopkins Applied Physics Laboratory (APL)

Location:

Laurel, Maryland Salary:

USD145,000

to

USD190,000

Job Type & Industry:

Data, Ai & Technology >

Ai & Technology Governance Contract Type:

Permanent Job Reference:

2997291151-2 Apply for this job now Job Description Johns Hopkins Applied Physics Laboratory (APL) seeks a Senior Air-to-Air Modeling and Simulation Analyst to develop, implement, and assess advanced models of air-to-air combat systems within the Data Science & AI Department. You will design high fidelity simulations, apply statistical and machine learning techniques, and perform complex data analysis to evaluate system performance and tactics. Collaborating with multi-disciplinary experts, you'll translate operational needs into analytic studies, present technical findings to sponsors, and help shape next generation defense capabilities in a mission-driven, research-focused environment that supports innovation, professional growth, and advanced study. Responsibilities Develop and refine high-fidelity air-to-air combat models and simulations Apply data science and AI techniques to assess system performance and tactics Design and execute simulation experiments and Monte Carlo analyses Validate, verify, and document complex models and analytic workflows Collaborate with cross-functional defense and aerospace teams and sponsors Translate operational and mission needs into analytic studies and simulations Prepare and present clear technical reports and briefings to stakeholders Support concept development for next-generation air-to-air systems Mentor junior staff in modeling, simulation, and analytical best practices Contribute to proposals, research initiatives, and technical publications Required Skills Air-to-air combat modeling and simulation Mathematical and physics-based modeling Python or MATLAB programming Statistical analysis and uncertainty quantification Machine learning and AI methods Monte Carlo simulation techniques Defense and aerospace system analysis Model validation and verification Data visualization and technical reporting Requirements analysis and experiment design