PhD Position (m/f/d)

Application deadline: 15/07/2026

• 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

• 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.

• 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

• 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

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.