Aero CFD & ML Intern - Hybrid

General Motors; High Wycombe; Hybrid; GBP 19,000 - 29,000; Full time

Job summary

GM Motorsports is seeking a Summer Intern to contribute to aerodynamic development. You may work on CFD workflows, wind-tunnel testing tools, and data-driven models, with opportunities to apply machine learning for performance prediction.

The role is hybrid and based at the Charlotte Technical Center in Concord, NC, with start dates in May or June. A strong foundation in aerodynamics, CFD, and scientific computing is preferred.

Qualifications

• Pursuit of a bachelor's degree in physics, mathematics, aerospace engineering, mechanical engineering, computational science, or closely related field.

Responsibilities

• Develop and improve CFD workflows across CAD preparation, geometry cleanup, meshing, solver execution, post-processing, and automated reporting.
• Develop tools and methods for wind-tunnel aerodynamic testing, including test planning, instrumentation, data acquisition, controls, and data processing.
• Develop and validate machine-learning or surrogate models that improve aerodynamic performance prediction and flow-field inference.
• Develop AI-enabled tools that improve engineering productivity, accelerate analysis, and support technical decision-making.
• Work with engineers and technical leaders to define requirements, evaluate results, document methods, and communicate recommendations.
• Projects will be defined by team needs and aligned with the candidate's experience, interests, and development goals.

Skills

Analytical skills

Quantitative problem-solving

Technical communication

Cross-functional collaboration

Education

Physics

Mathematics

Aerospace Engineering

Mechanical Engineering

Computational Science

Tools

CAD

Meshing

High-performance computing

CI/CD

DevOps

Job description

GM Motorsports is seeking a Summer Intern to contribute to aerodynamic development. You may work on CFD workflows, wind-tunnel testing tools, and data-driven models, with opportunities to apply machine learning for performance prediction.

The role is hybrid and based at the Charlotte Technical Center in Concord, NC, with start dates in May or June. A strong foundation in aerodynamics, CFD, and scientific computing is preferred.