Internship within Engineering (m/f) Aerodynamic Predictions with Machine Learning, Bremen

Airbus is a leading aircraft manufacturer with the most modern and comprehensive family of airliners on the market, ranging in capacity from 100 to more than 500 seats. Airbus champions innovative technologies and offers some of the world’s most fuel efficient and quiet aircraft. Airbus has sold over 13.800 aircraft to more than 360 customers worldwide. Airbus has achieved more than 8,000 deliveries since the first Airbus aircraft entered into service. Headquartered in Toulouse, France.

Tasks & accountabilities

For a test case where surface pressure information is available from CFD for a limited number of flow parameter variations; intermediate surface pressure solutions shell be approximated.

Different state of the art mathematical approaches shell be implemented and validated to build a multi parameter model to be benchmarked to a POD based approach.
Uncertainty quantification and Supervised Machine Learning will be key elements of the work.

The overall task is structured as follows:

• Study of state of the art approaches
• Implementation and validation
• Benchmark to conventional processes
• Documentation and presentation
• This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Required skills

• Enrolled student within Aerospace Engineering, Mathematics, Computer Science or similar field of study
• Advanced programming skills in Matlab and Python
• User experience with Linux
• English: Fluent