Computational Aeroelasticity Developer

Key Responsibilities

Computational Aeroelasticity & Aerothermoelasticity Development

Contribute to the development, verification, validation, and deployment of advanced aeroelastic simulation capabilities, including:

Low-Fidelity Methods

Panel methods, Doublet Lattice Method (DLM), and Vortex Lattice Method (VLM)

Generalized aerodynamic force generation

Linearized and frequency-domain aerodynamic modeling

Medium-Fidelity Methods

Hybrid CFD-panel methodologies

Reduced-order and surrogate modeling

Transonic correction techniques

Time-domain aeroelastic formulations

Flexible vehicle dynamic simulation methods

High-Fidelity Methods

CFD-based aeroelasticity using Euler and Navier-Stokes solvers

Fluid-structure interaction (FSI) and CFD-CSD coupling

Nonlinear aeroelasticity and aerothermoelasticity

High-speed and hypersonic aeroelastic analysis

Support The Development Of Solutions For

Static and dynamic aeroelasticity

Flutter prediction

Divergence and control reversal

Gust response and aeroservoelasticity

Buffet response and limit-cycle oscillations

Nonlinear aeroelastic behavior

Work with senior technical staff to transition advanced research concepts into production-quality commercial software.

Hypersonic & High-Speed Flight Simulation

Contribute to the development of simulation technologies for high-speed and hypersonic vehicle applications, including:

Hypersonic aerodynamics and aerothermodynamics

Shock-wave/boundary-layer interactions

Thermal-structural coupling and aerothermoelasticity

High-temperature flight environments

Flight stability and control at high Mach numbers

Participate in the implementation and validation of numerical methods such as:

Piston theory

Supersonic and hypersonic aerodynamic methods

Shock-expansion techniques

Reduced-order models

CFD-based aeroelastic methodologies

Prior research experience in one or more of these areas is highly desirable.

Multidisciplinary Simulation & Structural Dynamics

Collaborate with structural dynamics, CFD, and multiphysics development teams to build integrated simulation workflows.

Contribute To

Modal analysis and structural dynamics

Dynamic response analysis

Eigenvalue extraction methods

Coupled aerodynamic-structural simulations

Thermal stress and buckling analyses

Large-scale finite element modeling

Support Applications Involving

Commercial and military aircraft

Rotorcraft and UAVs

Hypersonic vehicles

Space and launch systems

Advanced aerospace and defense platforms

Scientific Software Development

Develop Robust And Scalable Commercial Software Capabilities, Including

Numerical algorithms and solver development

Scientific software architecture

APIs and workflow automation

Multiphysics integration frameworks

Verification and validation methodologies

Automated testing and continuous integration practices

Participate in the full software development lifecycle from research prototype to commercial product deployment.

High-Performance Computing

Contribute to the development and optimization of scalable simulation technologies using:

Parallel computing concepts

MPI, OpenMP, GPU, or accelerator technologies

Cloud and distributed computing environments

Optimize algorithms for large-scale engineering simulations and advanced aerospace workflows. Prior experience is beneficial but not required.

Customer & Industry Engagement

Work With Technical Experts, Product Teams, And Customers To

Understand aerospace simulation requirements

Support technical demonstrations

Education

Ph.D. with outstanding research experience in Aerospace Engineering, Mechanical Engineering, Applied Mechanics, Computational Engineering, or a related field.

Research specialization in computational aeroelasticity, aerodynamics, CFD, structural dynamics, or multidisciplinary simulation.

Experience

0–5 years of industrial experience, or equivalent graduate/postdoctoral research experience.

Demonstrated research experience in aeroelasticity spanning low to high speed flight regimes.

Experience developing research software, computational tools, or numerical simulation capabilities.

Ability to translate research concepts into practical engineering solutions.

Record of technical publications, research projects, or thesis work in relevant areas.

Technical Skills

Aerodynamics

Knowledge of potential flow methods, panel methods, DLM, or VLM

Understanding of subsonic, transonic, supersonic, or hypersonic aerodynamics

Familiarity with CFD fundamentals and numerical methods

Aeroelasticity

Coursework or research in flutter, dynamic aeroelasticity, gust response, or aeroservoelasticity

Familiarity with aeroelastic modeling and reduced-order methods

Exposure to aerothermoelasticity or high-speed aeroelasticity is a plus

Structural Dynamics & FEA

Modal analysis and structural dynamics fundamentals

Finite element methods and numerical analysis

Dynamic response and eigenvalue analysis

Software Development

Programming experience in C++ and Python.

Experience developing scientific or engineering software leveraging AI

Experience in software engineering best practices

High-Performance Computing

Familiarity with parallel computing concepts

Exposure to MPI, OpenMP, CUDA, GPU computing is desirable

Professional Skills

Strong analytical and problem-solving abilities

Passion for computational engineering and simulation technology

Ability to learn new technical domains quickly

Excellent written and verbal communication skills

Ability to work effectively in multidisciplinary teams

Customer-focused mindset with strong collaboration skills

Preferred Qualifications

Ph.D. research focused on computational aeroelasticity, aerothermoelasticity, CFD, structural dynamics, or hypersonics

Publications in recognized aerospace journals or conferences

Experience with commercial or research simulation tools such as MSC Nastran, Abaqus, ZAERO, FUN3D, SU2, SCFLOW, Fidelity, CHARLES, Fluent, STAR-CCM+, CFD++, or equivalent

Experience with multidisciplinary design optimization (MDO)

Exposure to machine learning, AI, or reduced-order modeling techniques

Experience with HPC environments and large-scale simulations

Participation in collaborative research programs with aerospace organizations, government laboratories, or universities

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