Intern
Pattern Recognition

Multiple Doctoral and Postdoctoral Researcher Positions (m/f/d) (100%, TV-L E13)

The Professorship for Pattern Recognition (University of Würzburg) invites applications for

multiple Doctoral and Postdoctoral Researcher Positions (m/f/d) (100%, TV-L E13, fixed term)

on machine learning and artificial intelligence in medical imaging and beyond.

The Pattern Recognition Group is a newly founded research group at the Center for AI and Data Science (CAIDAS) at the Julius-Maximilians-Universität Würzburg – and we are looking for PhD and postdoctoral researchers to join us! We have several open positions and are looking for your ideas, creativity, and contribution to shape the future of machine learning in medical imaging and beyond.

Open position (possible starting dates in parenthesis):

1. Doctoral researcher for machine learning for multi-contrast 7-T magnetic resonance imaging (May 2025):

This project is part of the DFG-funded research group MR biosignatures (https://www.dfg-for5534-mr-biosignatures.forschung.fau.de/) working on multi-contrast MRI to derive novel insights and advanced tissue characterization. You will be part of an interdisciplinary team, consisting of clinicians, physicists, computer scientists and engineers, working on reconstruction, registration, and analysis of multimodal MRI data. You will be able to develop and explore different machine learning approaches, including self-supervised / representation learning and physics-inspired machine learning.

For this position, prior experience with MR image generation, reconstruction, and analysis is a big plus, and students with e.g. thesis or project work in this field are particularly encouraged to apply.

2. Doctoral researcher for multimodal machine learning for endometriosis (July 2025):

Endometriosis is one of the most common gynecological conditions and can lead to chronic pain and reduced fertility. In Bavaria alone, approximately 50,000 cases are reported annually. In a multidisciplinary team consisting of 7 different labs at 4 institutions (FAU Erlangen-Nürnberg, University Hospital Erlangen, TU Munich and University of Würzburg), our innovative research focuses on integrating multimodal functional and structural noninvasive imaging methods with machine learning to create a comprehensive 3D pelvic model and provide early detection of endometriosis as well as surgical support. The model is further enriched with intraoperative and postoperative data to improve diagnostic and surgical outcomes.

Your tasks will include the integration and analysis of multimodal data sources, including registration, segmentation and unsupervised approaches. A particular focus will be on the analysis of histopathology data and the correlation with information from ultrasound, magnetic resonance imaging and endoscopy, and prior experience with one or more of these modalities is beneficial.

3. Doctoral or postdoctoral researchers in intraoperative imaging, domain generalization, active learning, data-efficient learning (May 2025 or later):

Based on existing work on active learning, data annotation, and medical image analysis, and domain generalization in our group, we want to take our research a step further and explore novel machine learning approaches and methods in this field.  Topics can be adapted to specific strengths and ideas of students interested in these projects, and you are invited to bring your own ideas. In case you are interested in this position, please highlight how your prior research aligns with the work at the Professorship for Pattern Recognition / the AIMI group.

We are currently establishing new collaborations at the University of Würzburg, among others with robotics, the Earth Observation Research Cluster, and the University Hospital Würzburg – providing the opportunity to contribute to different domains.

4. Postdoctoral Researcher within the Collaborative Research Center Exploring Brain Mechanics (available immediately)

See full job description here.

Additional information:

  • For PhD positions: Research on these projects can be carried out in the context of a Dr. rer. nat. at the Faculty of Mathematics and Computer Science at the University of Würzburg.
  • You will be part of a young, dedicated, and diverse team located in Würzburg and Erlangen, with the goal to address relevant questions in medical imaging and beyond.
  • You will be able to conduct interdisciplinary project work and have access to an extensive national and international network, with research partners in academia and industry
  • Postdoc and PhD positions are fully funded (100%, TV-L E13).
  • Positions may include teaching responsibilities, e.g., preparing and conducting exercises for lectures or seminars, and offer the opportunity to take on leadership roles for student projects.
  • Possibility for (part-time) remote work (home office).

Your profile (in addition to the qualifications mentioned above):

  • Above-average university degree (Master's or Diploma) / PhD degree (for postdoctoral positions) in computer science, engineering or a related field.
  • Proficiency in the fields of machine learning, computer vision, image analysis, e.g., shown also by courses / a thesis on a related topic.
  • Proficiency in Python (and ideally other programming languages), with strong coding and debugging skills.
  • Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow, or similar libraries.
  • Ability and willingness to work both independently and collaboratively on research questions, interest in working in highly interdisciplinary teams.
  • Strong communication skills, initiative, commitment, high sense of responsibility, and creativity.
  • Strong proficiency in English, both written and spoken.
  • Initial teaching experience (e.g., as a tutor) is a plus.
  • For PhD Students: Peer-reviewed publications at high-quality conferences or journals are a plus.
  • For Postdocs: Proven research experience, typically through peer-reviewed publications in high-quality journals and at ML/CV/Medical Imaging conferences.

You can find more information about us and our research here:

Professorship for Pattern Recognition, located at the Center for AI and Data Science (CAIDAS, Uni Würzburg):
https://www.caidas.uni-wuerzburg.de/pr/ (currently under construction)
https://www.aimi.tf.fau.de/ (our former website)
https://www.caidas.uni-wuerzburg.de/

We are committed to promoting equal opportunities. We aim to foster a collaborative and inclusive research environment where interdisciplinary ideas thrive. We welcome researchers from diverse backgrounds and encourage applications from those traditionally underrepresented in AI and healthcare. Female candidates are specifically encouraged to apply. Severely handicapped applicants will be given preferential consideration in the case of broadly equal suitability, ability and professional achievements.

Please send your application including a cover letter with interests, background (max. 1.5 pages), plus full CV and list of prior publications, as one PDF document via e-mail to Prof. Dr.-Ing. Katharina Breininger (katharina.breininger@uni-wuerzburg.de), head of the professorship for pattern recognition at the University of Würzburg. Additional attachments can include letters of reference from former supervisors, certificates, or transcripts. Please include [Application: Pattern Recognition Group <PhD/Postdoc>] in the subject line. Please indicate which position(s) you are interested in and highlight your expertise with regard to these positions.

Applications will be considered as they are received until positions are filled. Please send questions to the positions or the tasks to katharina.breininger@uni-wuerzburg.de.

Please note that the candidate evaluation involves one or more scientific-technical presentations and interview appointments to be held in person or via teleconferencing. Applications sent via e-mail will be confirmed within a week. Applications not complying with the above requirements may neither be confirmed nor considered.