Principal Aeroacoustics & Aerodynamics Engineer

This is a highly technical hands-on role for someone who wants to solve difficult multidisciplinary aerospace problems rather than incrementally improve established designs.

• Lead aerodynamic and aeroacoustic analysis and optimization of MagLev Aeros rim-driven electric and hybrid ducted fan systems.
• Model and predict fan rotor duct and integrated propulsion-system aerodynamic and acoustic performance.
• Develop designs that simultaneously optimize thrust efficiency noise weight and overall system performance.
• Apply CFD computational aeroacoustics reduced-order modeling optimization and other advanced simulation methods.
• Work with MAGGIE MagLev Aeros Multiphysics Aerospace Generative Graphical Inference Engine and advanced AI tools to accelerate design exploration and optimization.
• Develop and improve physics-based and data-driven models used within MagLevs multidisciplinary design environment.
• Correlate analytical and computational models with experimental and test data.
• Define test requirements and work with engineering teams to validate aerodynamic and acoustic performance.
• Collaborate closely with propulsion electrical mechanical controls motor thermal and systems engineers.
• Identify unconventional technical approaches and translate them into designs that can be built tested and ultimately commercialized.
• Serve as a technical authority in aerodynamics and aeroacoustics as MagLev advances its propulsion technology toward flight applications.

Qualifications :

• Advanced degree in Aerospace Engineering Mechanical Engineering Acoustics or a closely related field. PhD strongly preferred.
• Deep expertise in aerodynamics and aeroacoustics ideally involving propellers fans rotors turbomachinery ducted fans eVTOL or advanced propulsion systems.
• Strong background in CFD and computational modeling of complex aerodynamic systems.
• Experience predicting analyzing and reducing tonal and broadband aerodynamic noise.
• Understanding of rotor-stator interactions blade aerodynamics duct acoustics flow-induced noise and propulsion-system integration.
• Experience connecting simulation with physical testing and experimental data.
• Strong programming numerical modeling and engineering-analysis capabilities.
• Interest in applying AI machine learning optimization and generative engineering methods to aerospace design.
• Ability to operate independently and take technical ownership from initial concept through analysis testing and design iteration.

Additional Information :

All your information will be kept confidential according to EEO guidelines.

Remote Work :

No

Employment Type :

Full-time