Postdoctoral Researcher - Multimodal AI for Whole-Body PET/CT
Start Date
December 2026 or by arrangement
Employment Relationship
100%, fixed-term for three years
Institution / Workplace
Department for BioMedical ResearchUniversity of BernDepartment of Nuclear Medicine
Bern University Hospital
With us, you create value.
For yourself and for society.
For yourself and for society.
The project
With university affiliation through the DBMR, we develop multimodal AI for whole-body PET/CT, integrating imaging with clinical context to distinguish residual malignancy from inflammation or physiological uptake. The focus is lymphoma response assessment, with methods designed to transfer across tasks, diseases and institutions. You will work with over 14,000 available PET/CT examinations from Bern (>30 TB), linked reports, referrals and longitudinal studies, multicentre trial cohorts, and digitised histology in selected patients.Your responsibilities
- Shape research questions and develop multimodal methods combining PET/CT with clinical text, followed by longitudinal imaging and digitised histology.
- Develop context-aware image analysis and segmentation, multimodal representation learning and outcome prediction; explore physician-editable report generation.
- Lead projects from model design through multicentre clinical validation.
- Aim to publish in leading international journals and present at machine-learning and medical-imaging conferences.
- Contribute to follow-on grant applications and interdisciplinary collaboration.
Your profile
- PhD in computer science, machine learning, biomedical engineering or a related field.
- Strong deep-learning research on images; 3D/volumetric experience highly desirable.
- Excellent Python/PyTorch skills; reproducible pipelines at scale.
- Substantial methodological ownership and strong first-author publications.
- Ability to frame research questions, design baselines/ablations, identify leakage and shortcut learning, and communicate across disciplines.
- Particularly valuable: multimodal/vision-language learning, self-supervised pretraining or medical foundation models, longitudinal imaging, clinical NLP/report generation, computational pathology/whole-slide imaging, and distributed training.
- Prior PET/CT experience is not required; we provide clinical, biological and imaging expertise.
Your Benefits
- Meaningful work and fair compensation
- Strong research infrastructure and international network
- Interdisciplinary collaboration
- Access to cutting-edge technology and innovation
Working at the University of Bern
The University of Bern not only offers exciting tasks but also an environment that actively promotes development, diversity, and equal opportunities. Discover what makes us stand out as an employer and how you can grow with us.
Application and Contact
Interested candidates are requested to send a cover letter describing current and future research interests, a CV with publications, expected starting date, as well as contact information for two references or their reference letters, in one PDF file to robert.seifert@insel.ch.
Questions about the position?
Robert Seifertrobert.seifert@unibe.ch
Questions about the application?
Robert Seifertrobert.seifert@insel.ch