***Please note that you will primarily be working on site with a customer in Huntsville, AL along with some travel to Dayton, OH and Exton, PA***
We Are
Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.
You Are
You have spent a decade or more building and validating models that represent the real physics of missile defense systems, not simplified abstractions that look good in PowerPoint. You understand that a radar signature is not just a number in a spreadsheet, it is a time-varying, multi-spectral phenomenon shaped by flight dynamics, staging events, and sensor geometry, and you know how to represent that complexity in simulation environments that people actually trust.
You have sat in rooms with government customers, sensor engineers, and algorithm developers, and walked out with a shared understanding of what fidelity actually means for the problem at hand. You do not wait for perfect data. You build models from what exists, validate against what you can measure, and document the assumptions so the next person knows where the edges are.
You think in kill chains. You know that a high-fidelity trajectory model is only useful if it feeds realistic observables into the sensor sim, which feeds track data into the fusion layer, which informs the battle management decision. You have worked across that stack, and you know where the seams are.
At Ansys Government Initiatives, you will work on air and missile defense simulations that shape how the DoD evaluates threats, tests algorithms, and trains AI systems. The work is technical, the stakes are real, and the team expects you to lead.
What You'll Be Doing
Build high-fidelity models of threat trajectories, including staging events, flight dynamics, and multi-spectral signature behaviors across RF, IR, and other sensor-observable spectra
Develop and integrate radar phenomenology models that represent how different radar bands and sensor architectures detect, track, and characterize targets in realistic engagement scenarios
Support the creation of synthetic datasets for AI/ML training, including target-present and target-absent scenarios designed to reduce algorithmic bias and improve model robustness
Collaborate with signature characterization experts, sensor engineers, and government stakeholders to ensure simulation fidelity aligns with operational requirements and physics-based constraints
Implement sensing system models within frameworks like STK and AFSIM, representing track fusion, discrimination logic, and custody management across the missile defense kill chain
Provide technical leadership on modeling requirements, simulation architecture, and fidelity tradeoffs for emerging programs involving generative simulation and AI-enabled battle management
Integrate threat modeling and sensor simulations into larger analysis and experimentation environments used by DoD customers for system development and algorithm evaluation
The Impact You Will Have
Your models will directly inform how the DoD evaluates next-generation air and missile defense systems, shaping acquisition decisions and operational concepts
The synthetic datasets you generate will train AI/ML systems used for real-time threat discrimination, sensor fusion, and battle management decision support
Your expertise in radar phenomenology and signature modeling will ensure that simulations reflect the actual physics of sensing, not oversimplified assumptions that break under scrutiny
The simulation environments you build will enable government customers to test algorithms, evaluate system performance, and conduct mission-level analysis without relying…