Master student in the field of Supportability Engineering (d/f/m), (Engineer - Aerospace Engineering)

About us

Airbus is a pioneer of sustainable aerospace for a safe and united world. The company constantly works on innovations for efficient and technologically advanced solutions in the fields of aerospace, defense, and connected services. Airbus offers modern and fuel-efficient commercial aircraft as well as related services. Airbus is also a leader in Europe in the field of defense and security and one of the largest space companies in the world. In the helicopter sector, Airbus provides the world's most efficient solutions and services for civil and military helicopters. Job description

In order to support the Supportability Engineering team, Airbus Defence and Space is looking for a

Master student in the field of Supportability Engineering (d/f/m), thesis title “Machine Learning based Pattern recognition”

Are you looking for a master thesis? Then apply now! We look forward to you supporting us in the Supportability Engineering team as a master student (d/f/m)!

• Location: Manching
• Start: 01.11.2025
• Duration: 6 months

Your location

Located about an hour’s drive north of Munich, Manching is an up-and-coming market town that offers a wide range of leisure and cultural activities. Here, you can enjoy the quality of life in the countryside while the pleasures of nearby cities are still within easy reach.

Your benefits

• Attractive salary and work-life balance with a 35-hour week (flexitime).
• Traveling within Europe is possible after consultation and agreement from the department.
• International environment with the opportunity to network globally.
• Work with modern/diversified technologies.
• At Airbus, we see you as a valuable team member and you are not hired to brew coffee; instead, you are in close contact with the interfaces and are part of our weekly team meetings.
• Opportunity to participate in the Generation Airbus Community to expand your own network.

Thesis Topic

The work includes the definition, implementation, and evaluation of suitable machine learning models for analysing and classifying diagnostic patterns based on historical or simulated data from real-world testability use cases.

Your tasks and responsibilities

• Analyse and preprocess diagnostic data from test systems
• Identify characteristic failure patterns and symptom relationships
• Define and compare suitable model architectures for fault detection and isolation (e.g. decision trees, ensemble models, neural networks, clustering approaches, etc.)
• Train and validate models using established ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch) and MATLAB Simulink (e.g. Artificial Intelligence (AI))
• Evaluate model performance using metrics such as detection rate, false alarm rate, and isolation accuracy
• Integrate your approach into an existing analysis pipeline or tool environment
• Document and present your results to stakeholders

Desired skills and qualifications

• Full time enrolled student (d/f/m) in Computer Science, Electrical Engineering, Data Science, Mathematics, or a related field
• Solid understanding of machine learning concepts and data preprocessing
• Practical experience with MATLAB Simulink and ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch)
• Programming skills (e.g. Python)
• Interest in fault detection, diagnostics, and system testability
• Analytical mindset, structured working style, and ability to work independently
• Basic knowledge of test or diagnostic systems (e.g. FMEA/FMECA) is a plus
• Language skills: English fluent; French basic knowledge

Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate.

Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online (https://www.airbus.com/en/careers) now!

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

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus. Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.