Aero CFD Correlation Engineer - F1 Racing

Audi Revolut F1 Team; Bicester; On-site; GBP 80,000 - 120,000; Full time

Job summary

Audi Revolut F1 Team is seeking a Correlation Team member to join the CFD Group in Hinwil or Bicester. The role focuses on aligning CFD predictions with WT tests and real-world performance for the race car.

You will work with CFD methodology, Aero Performance and Aero Development groups, contribute to model validation and process improvements, and support data-driven decision making across aerodynamics projects.

Qualifications

• MSc or PhD in Mathematics, Mechanical Engineering, Aerospace Engineering, or related field with strong CFD focus.
• 3+ years of professional experience in race car aerodynamics development or performance evaluation, including CFD methods.
• Experience with CFD/experimental data analysis and comparison.
• Knowledge of CFD methods and their application.
• Experience with OpenFOAM and Linux environments.
• Familiarity with data science, ML/AI concepts is beneficial.

Responsibilities

• Work with CFD methodology, Aero Performance and Aero Development to increase CFD tool confidence for aero development of the race car.
• Contribute to understanding CFD model limitations and validate methodological improvements.
• Support overall CFD process and analysis tool improvements within the correlation group.
• Collaborate across CFD Group and wider Aerodynamics team to drive data-driven decisions.

Skills

CFD expertise

Aero performance mindset

Python programming

Data-driven decision making

Collaboration

Education

MSc or PhD in Mathematics, Mechanical Engineering, Aerospace Engineering or related field

Tools

OpenFOAM

CATIA V6/3DExperience

Linux

CAD software

Job description

Audi Revolut F1 Team is seeking a Correlation Team member to join the CFD Group in Hinwil or Bicester. The role focuses on aligning CFD predictions with WT tests and real-world performance for the race car.

You will work with CFD methodology, Aero Performance and Aero Development groups, contribute to model validation and process improvements, and support data-driven decision making across aerodynamics projects.