Application deadline: 15/07/2026
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Contribute to AI research in vascular imaging and shape the future of Giant Cell Arteritis (GCA) diagnosis!
The University Hospital Würzburg offers you the opportunity to actively contribute to the DFG-funded project "Artificial Intelligence-Assisted Diagnosis of Giant Cell Arteritis".
Giant Cell Arteritis (GCA) is a systemic vasculitis that can lead to severe complications, including vision loss and stroke, if left untreated. This project aims to develop a machine learning-driven automatic diagnostic tool to robustly detect and evaluate GCA in magnetic resonance images, thereby enhancing diagnostic accuracy and preventing GCA-related complications.
The Institute of Diagnostic and Interventional Radiology (Prof. Dr. Tobias Wech) is seeking to fill the position of a PhD Student (m/f/d, 65% TV-L) for this exciting project at the earliest possible date. The position includes the opportunity for a PhD or Dr. rer. nat. at the Graduate School of Life Sciences (GSLS).
We offer
The opportunity to work in an innovative, multidisciplinary DFG-funded research project with high clinical impact
The chance to develop cutting-edge AI methods for a clinically relevant application
Access to unique multi-center GCA MRI datasets and state-of-the-art computational resources
Presentation of your research at prestigious international conferences
A multidisciplinary team with experts in radiology, rheumatology, and AI
A stimulating academic environment with opportunities for further qualification
PhD or Dr. rer. nat. at the Graduate School of Life Sciences (GSLS)
Attractive remuneration according to TV-L E13 (65%), including annual bonus
Your Tasks
Development and implementation of machine learning algorithms for automated detection and segmentation of GCA in MRI scans
Pre-processing of multi-center GCA MRI datasets (2D T1-weighted and 3D CS-SPACE sequences) using super-resolution models and brain stripping
Training and evaluation of neural networks for semantic segmentation to identify inflamed vessels in extra-cranial arteries
Development of quantitative imaging biomarkers (e.g., vessel wall thickness, volume of inflamed segments) for disease activity assessment
Validation of methods using multi-center datasets from collaborating GCA centers (Freiburg, Ludwigshafen, Aarau)
Collaboration with clinical partners to ensure clinical relevance and applicability of developed tools
Publication of results in peer-reviewed journals
Presentation of research findings at international scientific conferences (e.g., ISMRM, RSNA, ECR)
Project Background
Giant Cell Arteritis (GCA) is a systemic vasculitis primarily characterized by inflammation of medium and large vessels, with a predilection for superficial cranial arteries (temporal, ophthalmic) and large intrathoracic vessels. If left untreated, GCA can lead to severe complications, including vision loss, stroke, aortic aneurysms, or dissection.
While MRI has emerged as a pivotal technique for comprehensive GCA imaging, the interpretation of advanced imaging protocols remains challenging. This project addresses these challenges by developing AI-driven automatic diagnosis to enhance diagnostic accuracy, efficiency, and standardization.
Building on a decade of GCA research and a unique data archive, we aim to create a machine learning-driven diagnostic tool that can be distributed free-of-charge to non-GCA centers, ensuring wide accessibility and improving patient outcomes worldwide.
Your Profile
Master’s degree in Computer Science, Medical Informatics, Physics, Engineering, or a related field
Experience in programming (e.g., Python) and relevant ML frameworks (e.g., PyTorch, TensorFlow)
Basic knowledge of MRI data processing and medical image analysis is a plus
Interest in semantic segmentation and computer vision techniques
Excellent written and spoken English
Independent, structured working style and strong problem-solving skills
Ability to work in an interdisciplinary team environment
This is what you can look forward to
Challenging, diverse and evolving area of responsibility
Attractive salary according to TV-L incl. annual special payment
Training and Continuing Education
Retirement Pension Plan
Company daycare center with extended opening hours
Company sports program
Flexible Working Hours
JobBike
Corporate Benefits
Become part of the team: Apply now!
Prof. Dr. Tobias Wech
Professor für Experimentelle Radiologie
Tel: +49931 201 46356
In the case of a university degree from a non-EU country, a long version of the certificate evaluation from the Central Office for Foreign Education is required.
Remuneration is in accordance with the relevant collective agreements. Severely disabled applicants will be given preference if they are otherwise equally qualified.
