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Thesis (f/m/x) - Operator Fatigue Assessment for Adaptive Automation in Air Traffic Control
Job Description
Req ID:  6778
Place of work:  Köln
Starting date:  Zum nächst möglichen Termin
Career level:  Student research project and final thesis
Type of employment:  Part time, Full-time
Duration of contract:  6 Monate

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 12,000 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 Software Technology sees software as a catalyst for research and innovation. The institute's staff, currently numbering around 200, make a significant contribution to advancements in the fields of aviation, space, energy, transportation, and security through the development of state-of-the-art software solutions and innovative research.

 

Our areas of competence include reliable and safety-critical software systems, artificial intelligence, high-performance computing and quantum computing, human-system interaction and visualization, software and systems engineering, as well as digital platforms and digital twins.

 

What to expect

The Intelligent and Trustworthy Systems department researches methods to make complex technical processes and systems – from software development to automated workflows and AI-assisted analysis – traceable, automatable, and interactively experimentally accessible. 

 

You will work in an interdisciplinary research group with an interest in operator state assessment in the context of Air Traffic Control, an area where fatigue is one of the key human factors for safety and workload management. 

 

As part of your thesis, you will conduct an extensive literature review on fatigue detection. This includes reviewing current measurement approaches and summarizing what data has been published. Possible research questions include the agreement/correlation between objective and subjective measures and their predictive validity for performance (e.g., reaction time, error rate), measurement biases/ biases (e.g., social desirability, sensor artifacts), as well as feature extraction and the use of these measures in machine learning-based classification (e.g., SVM, Random Forest, deep learning models) for fatigue or state assessment.

 

You will have the opportunity to shape the project according to your discipline, skills, and interests. Beyond the literature work, you may reanalyse open data, conduct an empirical study, or implement your concept as a demonstrator. 

 

Your tasks

  • Define and sharpen a concrete research question together with your supervisor.
  • Conduct a systematic literature review (e.g., following PRISMA guidelines) on objective and self-report fatigue measures to answer your research question.
  • optional extension: reanalysis of open datasets, design and execution of a small empirical study, or implementation of a prototype (e.g., signal-processing pipeline, dashboard, or classifier)
  • Document methodology and results in a structured, reproducible manner.

 

Your profile

  • enrolled in a Bachelor's or Master’s program in Computer Science, Human-Computer Interaction (HCI) or a related field
  • familiarity with (Bachelor level) or experience in (Master level) structured literature searches
  • self-motivated and reliable, able to work independently with regular supervisory guidance

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 6778) please contact:

 
Neele Duna 
Tel.: +49 2203 601 1099