Digital Twins in Autonomous Microfluidic Experiments

Modern microfluidic live-cell imaging is an emerging technology that aims to explore and investigate living microbial organisms to foster our understanding of microbial life, interactions between different microbial species and their reaction to environmental influences. This understanding is crucial for biomedical and biotechnological sciences, for example, to optimize biological processes or to develop the treatment for antibiotic-resistant microbial populations. Using automated microscopes and modern AI image processing technology enables the collection of quantitative and valuable data on microbial experiments at the scale of 100 GB/day and provides these deep insights at the single-cell level. Despite the unique opportunities, the plethora and amount of detailed data combined with automated experimentation system leads to a very complex interaction between biology, hardware and software.

Digital Twins have emerged as a key enabler for modern and complex I4.0 systems to collect, analyze and act on data but have not yet been established in microbial live-cell experimentation.

Within this project, we want to pair live-cell imaging with its digital counterpart into a digital twin in order to improve real-time experiment analysis, unlock new experimentation opportunities and start to build a smart and autonomous live-cell experimentation platform.

This work is performed within a research collaboration with the Institute for Systems Biotechnology (IBG-1) headed by Prof. Wiechert at Forschungszentrum Jülich.


  • Identification of the key components of digital twins and their applications (research)
  • Visiting the live-cell imaging facility at Forschungszentrum Jülich
  • Designing and modeling a digital twin architecture/concept for the live-cell imaging application
  • Testing the application of the digital twin in a prototyping system

Our offer:

  • A highly interdisciplinary project with impact on state-of-the-art microbial research
  • Cross-domain supervision by the groups at RWTH Aachen and Forschungszentrum Jülich
  • Experience in performing original scientific work and, ideally, publishing your work at scientific conferences
  • Comprehensive and individual support

Your profile

  • Pursuing a Master’s degree in Computer Science, or closely related field
  • Interest in life science, data science and modeling
  • Motivation, independence and commitment
  • Strong programming skills (python, Java)
  • Good written and oral communication skills of German or English
  • (Optional) Lecture Model-based Software Engineering/ Model-based Systems Engineering

Contact persons

Interested in the topic? Find out more with our publications about our current research on digital shadows and digital twins.

For more information please contact us with your application documents to Malte Heithoff (Mail: or Johannes Seiffarth (Mail:

Task definition:

Prof. Dr. Bernhard Rumpe
Lehrstuhl Software Engineering
Ahornstr. 55
52074 Aachen

Prof. Dr. Wolfgang Wiechert
Institute of Bio- and Geosciences (IBG)
Biotechnology (IBG-1)
Forschungszentrum Jülich GmbH
52428 Jülich