Masterstudent/in (w/m/d): Informatik, Machine Learning, Data Science - Forschung, Ingenieur

About

The Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne conducts interdisciplinary life science research with innovative approaches at the highest international level. The goal is to maintain and improve human health and performance in a mobile society – in space, aviation, and on Earth.

What to expect

The "Sleep and Human Factors" department at the Institute of Aerospace Medicine researches, among other things, how fatigue and overload can impair the cognitive performance of operators, whether and how modern systems (e.g., with AI support) actually relieve an operator, and much more. If you are interested in the working environments of the future and wonder where humans fit into all this technology, then you are in the right place.

Increasingly, physiological data can be used for the immediate and continuous assessment of mental states, such as fatigue or workload. An important study-based indicator for determining current mental workload is heart rate variability (HRV) from the ECG. Furthermore, eye movement metrics, such as blink frequency, fixation duration, or saccade speed, are used to assess workload. As part of a larger project, a platform-based collection and evaluation of such data is planned. The aim is to prepare the setup of a study to investigate remote operators in rail transport so that HRV and eye movement data from the participants can be smoothly recorded and evaluated in autumn 2026. To this end, smaller pilot studies for system validation are to be conducted in spring 2026.

Your tasks

• Further development of existing preprocessing algorithms based on already collected physiological ECG and eye movement data
• Calculation of time and frequency domain measures of heart rate variability
• Use of Machine Learning models to recognize the operator's state, especially fatigue

What you bring

• Completed Bachelor's degree in Computer Science, Machine Learning, Data Science, Medical Informatics, or equivalent
• Very good knowledge of Python
• Experience in Machine Learning and with common ML libraries (e.g., Scikitlearn, Catboost) and models
• Experience with the processing of physiological or behavioral data
• Enthusiasm for aerospace and human factors
• Willingness to familiarize yourself with new topics, try out new technologies, and develop them independently
• High team spirit and very good German and English skills

If you consider your programming skills sufficient, we also welcome applications from other educational backgrounds (Psychology, Engineering, etc.). We look forward to getting to know you!

Questions about this position (Reference number 3974) can be answered by: Christian Mühl Tel.: +49 2203 601 3121