opengreenhouselsvp
Aerodynamic UAV Simulation Engineer
Helsing
LocationMunich
Last observed2026-06-13 05:24:22.107953
Job idlsvp-helsing:greenhouse:4876439101
Who we are Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards. As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously. We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications. The role As Aerodynamic UAV Simulation Engineer, you will own the aerodynamic analysis and characterisation of current and future drone platforms, combining high-fidelity CFD with fast-running low-fidelity methods to support design decisions across the full development cycle. You will generate and maintain aerodynamic databases that feed directly into flight dynamics, control law and simulation workflows, and validate simulation outputs against physical test data. Working at the intersection of computational analysis and hands-on test, your work shapes airframe design from early concept through to flight-ready hardware. The day-to-day Build, calibrate and run low-fidelity aerodynamic models using Panel Methods, Vortex Lattice Methods and 2D boundary layer tools to rapidly evaluate early-stage concept designs, while executing high-fidelity 3D CFD simulations to resolve complex flow behaviours including rotor-wing interactions and fuselage drag Generate, maintain and deliver comprehensive aerodynamic databases to Flight Dynamics, Control Law and Simulation teams, ensuring data quality and traceability meet programme requirements at each design milestone Define and plan physical test setups, including wind tunnel campaigns, ground benches and flight test manoeuvres, executing validation tests in close collaboration with the Test Department and correlating sensor data back to simulation models to improve solver accuracy Participate in airframe design reviews, providing quantitative aerodynamic feedback and guidance to Mechanical and Systems Engineering teams that directly informs structural and configuration trade-off decisions Contribute to the automation of the simulation pipeline by scripting CAD-to-solver workflows in Python or MATLAB, reducing manual effort and accelerating design iteration cycles You should apply if you Have analysed and characterised aerodynamic performance of UAVs or light aerospace systems using both low-fidelity tools such as OpenVSP/VSPAERO, XFLR5/XFOIL and AVL, and commercial CFD packages such as ANSYS Fluent, StarCCM+ or OpenFOAM Have planned and executed physical validation test campaigns, including sensor instrumentation setup and post-test data correlation, bridging simulation outputs and measured results into improved solver accuracy Apply a strong working understanding of subsonic flight mechanics, boundary layer physics, wing design and rotorcraft-induced flow fields to inform practical design decisions Write scripting workflows in Python or MATLAB that automate simulation processing, geometric parametrisation and data visualisation across complex aerodynamic analyses Act decisively with minimal guidance, own outcomes end-to-end and initiate solutions without waiting for direction Note: We operate in an industry where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points. Nice to Have Experience contributing to conceptual airframe design trade studies, translating aerodynamic data into configuration-level recommendations f
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