Doctoral Student / PostDoc: The Chair of Explainable Machine Learning at the Otto-Friedrich-Universität Bamberg is inviting applications for one Doctoral Student (m/f/d) or PostDoc (m/f/d) position (TV-L E13, full-/part-time). The position focuses on developing advanced machine learning methods with a strong emphasis on interpretability, robustness, and tangible real-world impact in fields such as medical imaging and healthcare.
Chair of Explainable Machine Learning
Otto-Friedrich-Universität Bamberg
📊 Summary Table
| Field | Details |
|---|---|
| Designation | Doctoral Student – Scientific Employee (m/f/d) OR PostDoc – Scientific Employee (m/f/d) |
| Research Area | Explainable Machine Learning, Robustness & Generalization, Data-efficient Algorithms, Self-Supervised & Representation Learning, Medical Imaging |
| Location | Chair of Explainable Machine Learning, Otto-Friedrich-Universität Bamberg (ERBA Campus), Germany |
| Duration | 3 years (Doctoral Student) / 2 years (PostDoc), extension possible |
| Employment Type | Full-time or Part-time (TV-L E13) |
| Application Deadline | 1 October 2025 (priority review); applications accepted until filled |
| Contact | Prof. Dr. Christian Ledig – christian.ledig@uni-bamberg.de |
🎓 Eligibility / Qualification
- Doctoral Student: Excellent university degree (MSc) in machine learning, pattern recognition, image/signal processing, applied mathematics, statistics, or related fields.
- PostDoc: PhD in the above-mentioned fields with a strong research track record and published work.
- Proficiency in programming (Python, C++ or equivalent).
- Strong analytical, structured, and independent working style.
- Excellent English skills (German helpful, not mandatory).
- PostDoc applicants should demonstrate strong publication records.
📝 Job Description
- Contribute to research and teaching activities at the Chair of Explainable Machine Learning (ERBA Campus).
- Conduct independent research in one of the focus areas:
- Robustness & generalization of neural networks / Outlier Detection
- Data-efficient algorithms / Self-supervised learning / Representation learning
- Image Reconstruction / Segmentation / Object Detection
- Medical Image Analysis and AI system evaluation
- Publish and present results at leading international conferences (e.g., CVPR, ICCV, ECCV, AAAI, MICCAI).
🌍 Additional Information
- The position is family-friendly, suitable for part-time, and allows partial remote work if tasks permit.
- The university actively promotes gender equality and encourages applications from qualified women.
- Applicants with disabilities will be given preference if equally qualified.
📬 How to Apply
Send your complete application as a single PDF file including:
- Motivation letter
- CV
- Transcripts
- (Optional) Research project proposal, publication list, contact details of two references
to: Prof. Dr. Christian Ledig (christian.ledig@uni-bamberg.de)
📅 Deadline: Applications received until 1 October 2025 will be reviewed by 10 October 2025. Later applications will be considered until the position is filled.
📍 Address:
Otto-Friedrich-Universität Bamberg
Chair of Explainable Machine Learning
An der Weberei 5
D-96047 Bamberg, Germany
