STEM Master Thesis (M/F/D) - MINT Masterarbeit (D/M/W) - Apply now to work on your Master thesis in the frame of Fleet Data Analysis!

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Job Description

Are you looking for a final year project? Join us to work on your Master thesis in the frame of Fleet Data Analysis!

Location: Hamburg

Start: winter semester 2022

Duration: 6 months

Our Team

We are a mixed team of aeronautical and general engineers, physicists and mathematicians from several countries.

Currently, we are 6 females and 8 males, all having years of experience in aircraft design and particular overall aircraft and component loads.

Activities of our team are manifold and deal amongst others with the development of a digital twin for the flying aircraft to support fatigue analysis, fleet survey and AC maintenance.



Our Department/Domain

The Loads & Aeroelastic department is part of the Airbus Flight Physics Centre of Competence and hence at the heart of aircraft design. We are combining the disciplines Aerodynamics, Flight Mechanics, Structures and Control Theory to create a digital model for Loads computations. We support the aircraft design during concept, development and certification phase. We calculate high quality data with in house developed methods and tool and supply these results to the design teams created.

Your Master Thesis

Fleet Data Analysis - Investigation of Fleet Survey Data to improve Fatigue Design Assumptions

Often the fatigue design of commercial aircraft is based upon assumptions about its future usage. Certification specifications (CS 25.571) offer two ways for usage assumptions: either design for most severe usage or design for typical usage. Designing the aircraft based on typical usage implies the obligation of ensuring that the product usage finally complies with the design intention. As a consequence recurring fleet surveys need to reliably capture the overall aircraft usage.

The analysis to be performed is based on public data (only trajectory data, but complete coverage) and Airbus data (subsets only, but more parameters) made available in the big data platform Skywise (https://aircraft.airbus.com/en/services/enhance/skywise). One of the goals of this platform is reducing the risks of aircrafts on ground events (including the topic of high load events (https://safetyfirst.airbus.com/high-load-event-reporting). The available data sources in the Skywise platform are various (operational, statistical) and their combination often yields new insights.

Your thesis covers the set-up and evaluation of different machine learning models for further analysis of the data and the identification of dependencies. The aim is to identify which parameters of interest can be modeled based on public data. For instance it might be necessary to estimate the aircraft weight only based on its trajectory.

The usage of a public dataset allows a better coverage of worldwide flights as well as airlines and enables to address the changes in global flight traffic due to the Covid-19 pandemic period.

Your analysis comprises the comparison of results with the baseline study, which is kept up-to-date by considering new flights.

The Individual Steps Will Be

• Develop routines to identify/correct data errors
• Set up different Machine Learning Models
• Evaluate and assess these models
• Identify changes during Covid-19 pandemic period
  
  

Your Profile

• Enrolled full time student (d/f/m) within Science, Technology, Engineering & Mathematics or similar field of study
• You bring genuine interest in Airbus and our products.
• You are keen to understand physical aspects and to develop yourself
• English: fluent
• Programming skills preferably in Python & SQL knowledge would be a plus
  
  

You are a good team player, have excellent communication skills, and are able to work independently.

Does this job description fit your objectives and profile? Take the next step in your career and come and join us!

Please Provide The Following Documents

cover letter, C.V., relevant certificates, current certificate of enrollment

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

Contract Type

Final-year Thesis / Stage fin d’étude / Abschlussarbeit / Proyecto fin de carrera

Experience Level

Student / Etudiant / Student / Estudiante

Job Family

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.

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.