Postdoctoral Researcher - Multimodal AI for Whole-Body PET/CT — Universität Bern

Full description

UniBE is interconnected. With us, you're part of an international community and benefit from interdisciplinary collaboration.

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.

Meaningful work and fair compensation Application and Contact Interested candidates are requested to send a one-page note identifying the research question you would most want to pursue here and how you would test it, a CV with publications, expected starting date, as well as contact information for two references or their reference letters, in one PDF file to [email protected]. With us, you create value. 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

Your profile

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Your Benefits

Strong research infrastructure and international network Interdisciplinary collaboration Access to cutting-edge technology and innovation Other benefits

Working at the University of Bern

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