Fixed-term contract for 3 years | Full-time, 38.5 hours per week | Salary according to TV-L E13 | Institute of Neuropathology

We are UKM. We have a clear social mission and, with our focus on healthcare, research, and teaching, we bear a unique responsibility.

To meet our high standards every day, we are looking forward to your expertise in AI and computer vision at the Institute of Neuropathology. We develop deep learning methods that improve the diagnostic yield of brain biopsies – ideally with you on board!

RESEARCH PROJECT: DISEASE RECOGNITION FROM REACTIVE CNS TISSUE

Brain biopsies may contain only reactive tissue adjacent to a lesion, preventing a definitive diagnosis by conventional histopathological assessment. Our project uses pathology foundation models and weakly supervised deep learning to recognise the underlying disease in such tissue from whole-slide images (preprint: arxiv.org/abs/2609.02390).

The project will be carried out in close collaboration with the Computer Vision and Machine Learning Systems group at the University of Münster (Prof. Dr. Benjamin Risse and Dr. Jan Ernsting), providing an interdisciplinary environment for developing and applying advanced AI methods to clinically relevant challenges.

RESPONSIBILITIES:

• Develop machine learning approaches for histological whole-slide image analysis, including weakly supervised classification using pathology foundation models and multiple instance learning (MIL)
• Build reproducible pipelines for image preprocessing, quality control and feature extraction
• Evaluate model robustness, bias and generalisation across centres, scanners and frozen sections, and apply interpretability methods
• Manage the digital pathology infrastructure of the institute (slide scanners, computing servers)
• Contribute to prospective observational evaluation, reproducible research software, scientific publications and conference presentations

REQUIREMENTS: 

• A Master's degree or equivalent qualification in computer science, data science, mathematics, bioinformatics or a related discipline
• Strong theoretical foundations in machine learning and computer vision
• Practical experience with Python programming and deep learning frameworks
• Interest in rigorous statistical evaluation and reproducible scientific research
• An independent and structured working approach, strong communication and teamwork skills, and enthusiasm for interdisciplinary research
• Good written and spoken English skills
• Experience with large image datasets, computational pathology, foundation models, multiple instance learning or image registration is an advantage

Prior medical knowledge is not required.

WE OFFER:

• Salary according to TV-L E13, extra annual payment, and company pension plan (VBL)
• 30 days of vacation per year, plus two additional days off on Christmas Eve and New Year's Eve
• A wide range of training and professional development opportunities
• A respectful and appreciative work environment within a diverse team
• Support and advisory services for health and work-life balance
• Additional benefits such as sports programs, job ticket, jobrad, company events, cafeteria, and emergency childcare

ADDITIONAL RESEARCH BENEFITS:

• An opportunity to address a clinically relevant challenge at the intersection of AI, computer vision, neuropathology and molecular research, with the potential for meaningful clinical impact
• Close collaboration with internationally recognised research groups specialising in AI, neuropathology and molecular research, as well as an established network of partner neuropathology centres
• An interdisciplinary research environment with established analysis workflows and access to extensive histological image datasets
• Opportunities to develop innovative methodological approaches and shape your own research directions

For inquiries, please contact: Prof. Dr. Christian Thomas, Institute of Neuropathology, christian.thomas@ukmuenster.de or Prof. Dr. Benjamin Risse, Institute for Geoinformatics and Department of Computer Science, b.risse@uni-muenster.de

Apply now via our career portal.