Aerospace Research Engineer

Define and validate meaningful aerodynamic problems for physics AI models, connecting model development with real aerospace engineering needs.

• Define aerodynamic cases across flight conditions and geometries.
• Establish physical requirements and model evaluation criteria.
• Analyze lift, drag, pressure, boundary layers, and flow separation.
• Evaluate performance over Reynolds number, Mach number, and angle of attack.
• Compare model predictions with CFD, analytical, and experimental references.
• Identify physical failure modes and operating limitations.
• Translate aerospace use cases into reproducible research problems.

• Aerospace, mechanical, or related engineering background.
• Strong aerodynamics and fluid mechanics knowledge.
• Numerical simulation and engineering analysis experience.
• Python, MATLAB, or similar scientific tools.
• Ability to evaluate physical validity and communicate assumptions.

• High-speed, transonic, supersonic, or hypersonic flow.
• Turbulence models and compressible flows.
• OpenFOAM, Fluent, STAR-CCM+, SU2, or PyFR.
• UAVs, aircraft, wind-tunnel validation, or aerospace R&D.

Establish validated aerospace cases and model performance standards relevant to engineering practice.

Send your CV and a relevant paper, technical project, GitHub repository, or portfolio to careers@ratiolabs.ai. Suggested email subject: “Aerospace”.