Master Student (d/f/m) Airframe Fatigue Analysis

Job Description:

Master Thesis - Exploration of the Domain of Validity for Multiaxial Fatigue Analysis Criteria  

Location: Hamburg (Finkenwerder / ZAL)

Start Date: 01.09.2026

Duration: 6 months

About Us

Are you looking to bridge the gap between academic research and cutting-edge industrial application? Airbus Operations is seeking a motivated Master’s student (d/f/m) to join our R&T NSDW Integration team. You will be fully embedded within a transnational Research & Technology (R&T) team of Structural Analysis specialists working on the Next Generation Aircraft.

Your Work Environment & Benefits

Work-life balance with a 35-hour week (flexitime).

Mobile working after agreement with 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.

We treat you as a full-fledged team member. You will participate in weekly team meetings, collaborate with various engineering interfaces, and network globally.

Gain hands-on experience with modern, diversified technologies and state-of-the-art simulation tools.

You will work at Airbus' largest civil aircraft production site in Hamburg Finkenwerder. Enjoy a unique workplace on the banks of the river Elbe, with the option to commute by ferry and experience Hamburg's vibrant maritime culture.

The Challenge (Thesis Background)

While analytical approaches for fatigue calculation guarantee a minimum fatigue life and work excellently for simple analytical sizing and generic metallic structures, there is significant room for optimization in complex structures. In this regard, Airbus is actively studying methods to evaluate multiaxial stress fields via modern 3D finite element analysis. Your thesis will contribute to validating these new approaches for integration into future Airbus fatigue assessment methods. 

Your Tasks and Responsibilities

During your 6-month thesis, you will:

Evaluate fatigue criteria tailored to detailed, high-fidelity simulations.

Utilize Python to process complex simulation data and evaluate the limits/domains of validity for new methods.

Work closely with the structural analysis team and document your findings for potential integration into future industrial sizing methods.

Desired Skills and Qualifications

Enrolled full-time Master’s student (d/f/m) in Aerospace Engineering, Mechanical Engineering, Structural Mechanics, or a similar field of study.

Sound basic knowledge of overall aircraft design and strong foundational skills in Finite Element Modeling (FEM).

High proficiency in Python for data processing, scripting, and automation.

Analytical thinking, problem-solving skills, and the ability to work autonomously within a research-driven environment.

Proficiency in English (written and spoken) is required.

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 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.

Company: Airbus Operations GmbH

Employment Type: Final-year Thesis

Experience Level: Student

Job Family: Support to Management <JF-FA-ES>

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Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com.

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.