Bachelor's degree in Aerospace Engineering or related field.
5+ years of experience in modeling and simulation, preferably in aerospace.
Strong proficiency in Python programming.
Familiarity with AFSIM or similar aerospace simulation tools.
Solid understanding of orbital mechanics and space systems.
Experience with phenomenological models and validation of those models.
Responsibilities
Define modeling requirements from user needs and system architecture; develop automation scripts.
Develop end-to-end phenomenology chain models, including complex EO/IR target signatures.
Oversee mission-level simulation to assess ISR constellation performance.
Conduct trade studies on future ISR constellations.
Assess resilience of specific ISR architecture; model impacts of space environment on payload performance.
Utilize Python for model development and simulation execution.
Leverage AFSIM for analysis and performance prediction.
Benefits
Cutting-edge projects in the aerospace domain.
Opportunity to work with a critical government client.
Onsite presence in Chantilly, VA for team collaboration.
Full Job Description
Position Title: Modeling & Simulation Engineer Position Type: Full-time; Onsite Position Location: Chantilly, VA Clearance Required: Active TS/SCI CI Poly
Waypoint's client is seeking a highly motivated and skilled Modeling & Simulation Engineer to join their team supporting a critical government client. This position offers the opportunity to work on cutting-edge projects within the aerospace domain.
Responsibilities:
Define modeling requirements from user needs and system architecture and develop scripts to automate scenario modeling and performance analysis.
Develop models of the end-to-end phenomenology chain, including generating complex EO/IR target signatures (BRDF, thermal), modeling atmospheric radiative transfer using tools like MODTRAN, and integrating realistic cloud clutter and terrain backgrounds.
Oversee mission-level simulation to assess ISR constellation performance.
Conduct trade studies on future ISR constellations.
Assess the resilience of specificized ISR architecture; model the space environment's impact on payload performance, including radiation effects on focal plane arrays, and analyze the vulnerability of established PNT (Positioning, Navigation, and Timing) systems to RF interference.
Utilize Python for model development, data analysis, and simulation execution.
Leverage AFSIM (or similar aerospace simulation software) for analysis and performance prediction.
Incorporate phenomenological modeling principles into relevant models and simulations.
Required Qualifications:
Active TS/SCI clearance with Poly.
Bachelor's degree in Aerospace Engineering or a related field.
5+ years of experience in modeling and simulation, preferably within the aerospace industry.
Strong proficiency in Python programming.
Familiarity with AFSIM or similar aerospace simulation tools.
Solid understanding of orbital mechanics and space systems.
Experience with phenomenological models, including a demonstrated ability to model relevant physical phenomena and validate those models.
Experience modeling solar illumination effects, thermal emissions, Bidirectional Reflectance Distribution Function (BRDF) for material identification, and temperature dynamics of a target.
Experience modeling Radar Cross Section (RCS) for various frequencies and polarizations, and the signatures of active RF emitters.
Experience with atmospheric models (like MODTRAN or LibRadtran) to simulate absorption, scattering, turbulence (seeing effects), and path radiance.
Experience generating realistic backgrounds, including Earth limb radiance, cloud clutter models, terrain-specific thermal and optical properties, and celestial backgrounds (stars, zodiacal light).
Excellent communication and teamwork skills.
Preferred Qualifications:
Master's degree in Aerospace Engineering or a related field.
Experience with other simulation tools and programming languages.
Experience with non-cooperative target tracking.
Experience with collection & revisit modeling.
Experience modeling the dynamics of rapid slewing and settling of the spacecraft bus and pointing systems.
Demonstrated experience modeling the end-to-end Synthetic Aperture Radar (SAR) chain.
Knowledge of cloud computing platforms (e.g., AWS, Azure).
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