We are currently reorganising our job portal. During the transition phase, you can find more jobs here: previous DLR job portal
Apply now
Master Thesis or Working Student (f/m/x) Development AI Fault Detection Framework Train Localization
Job Description
Req ID:  3604
Place of work:  Oberpfaffenhofen
Starting date:  01.03.2026
Career level:  Student employment, Internship, Student research project and final thesis
Type of employment:  Part time
Duration of contract:  3 to 6 Months

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 11,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The DLR Institute of Communications and Navigation is dedicated to mission-oriented research in selected areas of communications and navigation. Its work ranges from the theoretical foundations to the demonstration of new procedures and systems in a real environment and is embedded in DLR's Space, Aeronautics, Transport, Security and Digitalization programmes.

 

What to expect:

At the DLR Institute of Communications and Navigation we conduct research on different methods for precise and reliable localization of trains. To evaluate these methods, we have collected data from different kinds of sources (e. g. video cameras, GNSS receivers, magnetic field sensors, accelerometers). To evaluate our data in an efficient way, we want to build a framework to compare data from different sources with a focus on detecting and explaining sensor faults.

 

Your tasks:

Depending on your qualifications, your tasks can include:

  • Programming a unified framework containing sensor and video data from different sources
  • Integration of AI tools (e. g. video object detectors like YOLO or open-source LLMs) into the toolchain and/or adaption of AI tools to the railway domain
  • Evaluation of measurement faults in sensor data using the developed framework
  • Application of fault detection methods to train localization

 

Your profile:

  • Study of Computer Science, Software Engineering, Information Technology, Data Science, Geodesy or similar
  • good programming skills in Python and/or Matlab
  • Hands-on experience with machine learning tools
  • Knowledge about fault detection methods is not necessary, but can be beneficial
  • Ability to work independently

 

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

 

We look forward to getting to know you!

 

If you have any questions about this position (Vacancy-ID 3604) please contact:

 

Stephan Sand 
Tel.: +49 8153 28 1464 
Apply now