Creating knowledge. Making a difference. Shaping the future. This is what the University of Münster stands for as one of the strongest research-oriented universities in Germany and one of the largest employers in the region. Every day, over 7,000 employees devote themselves to cutting-edge research and excellent teaching. We share more than a workplace. We share the desire to make a real impact – regionally and internationally. Our day-to-day work is distinguished by diversity, openness and space to pursue one’s ideas. Become a part of our team – in academia, a technical or manual trade, or administration.
The Computer Vision and Machine Learning Research Group at the Institute for Geoinformatics at the University of Münster is seeking to fill the following position of a

Doctoral Research Associate (Wissenschaftlicher Mitarbeiterin, salary level E 13 TV-L)

**for the externally funded project Collaborative Research Centre 1450 inSight at the earliest possible date. We are offering a fixed-term full-time position (100%) for 3 years. Full-time employees are required to teach 4 hours per week during the semester.

The position is located in the research group of Prof. Benjamin Risse and focuses on the development of computer vision, machine learning, and explainable AI methods for complex biomedical imaging data. The project aims to quantify hypoxia, immune cell infiltration, vascular structures, and tissue damage across scales, using multimodal data from light sheet fluorescence microscopy, PET/MRI, and intravital imaging.

Project Description:

The project focuses on developing and applying novel machine learning-driven computer vision approaches for biomedical multi-scale image analysis. In particular, you will develop algorithms for efficient annotation, segmentation, tracking, feature extraction, and explainable analysis of large volumetric 3D and 4D datasets. A central goal is to enable quantitative analysis of hypoxia and inflammation in chronic and acute disease models, including glioma and stroke.**

Your tasks:

• Developing tailored computer vision and machine learning algorithms for biomedical image analysis
• Implementing deep learning-based segmentation methods for large-scale 3D and 4D volumetric imaging data
• Developing eye tracking-based annotation strategies for efficient interactive labelling of complex biomedical structures
• Adapting foundation models, prompt-based segmentation methods, and transformer architectures to biomedical multi-scale datasets
• Implementing feature extraction and quantitative analysis pipelines for hypoxia, vasculature, immune cell infiltration, and tissue damage
• Integrating explainable AI strategies to validate and interpret model predictions
• Collaborating closely with biomedical researchers, imaging experts, and clinicians within an interdisciplinary research environment
• This position is tied to working towards a doctorate (PhD in Computer Science or Geoinformatics)

Our expectations:

• Master’s degree in Computer Science, Geoinformatics, Physics, Mathematics, or a related quantitative field
• Strong interest in machine learning, deep learning, computer vision, and biomedical image analysis
• Interest in large-scale volumetric data, 3D/4D image processing, foundation models, and explainable AI
• Experience with Python and deep learning frameworks such as PyTorch or TensorFlow
• High motivation for scientific work and willingness to contribute to an interdisciplinary team
• Excellent English communication skills (spoken and written); German skills are advantageous

Advantages for you:

• The opportunity to work and complete a dissertation at the cutting edge of AI, computer vision, and biomedical imaging
• A highly interdisciplinary project combining artificial intelligence, advanced microscopy, multimodal imaging, and inflammation research
• Access to unique biomedical imaging datasets and close collaboration with experimental research groups
• Competitive, international, and collaborative research environment
• Structured PhD training and broad professional development opportunities
• Salary according to tariff agreement, extra annual payment, and company pension plan (VBL)
• A respectful and appreciative work environment within a diverse team

The University of Münster strongly supports . We welcome all applicants regardless of sex, nationality, ethnic or social background, religion or worldview, disability, age, sexual orientation or gender identity. We are committed to creating family-friendly working conditions. Part-time options are generally available.

We actively encourage applications by women. Women with equivalent qualifications and academic achievements will be preferentially considered unless these are outweighed by reasons which necessitate the selection of another candidate.

For inquiries, please contact: Prof. Benjamin Risse, , +49 251 83-32717

Are you interested? Then we look forward to receiving your application by 2026-07-24.

Please send us your application electronically in PDF format including:

• Letter of motivation (max 2 pages)
• Summary of your Master‘s thesis (max 1 page)
• Transcript and scanned copies of your degree certificates
• Two letters of recommendation and/or names and contact details of two references

Please note that we cannot consider other file formats.

Reference number: 2026_07_09