Postdoc: Multimodal AI for Whole-Body PET/CT Imaging

University of Bern; Bern; Vor Ort; CHF 90.000 - 130.000; Vollzeit

Zusammenfassung

University of Bern in Bern seeks a computational imaging researcher to shape research questions and develop multimodal methods combining PET/CT with clinical text, followed by longitudinal imaging and digitised histology. You will lead projects from model design through multicentre clinical validation and aim to publish in leading journals.

You will develop context-aware image analysis and segmentation, multimodal representation learning and outcome prediction; explore physician-editable report

Qualifikationen

• PhD in computer science, machine learning, biomedical engineering or related field.
• Strong deep-learning research on images; 3D/volumetric experience 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.

Aufgaben

• 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.

Jobbeschreibung

University of Bern in Bern seeks a computational imaging researcher to shape research questions and develop multimodal methods combining PET/CT with clinical text, followed by longitudinal imaging and digitised histology. You will lead projects from model design through multicentre clinical validation and aim to publish in leading journals.

You will develop context-aware image analysis and segmentation, multimodal representation learning and outcome prediction; explore physician-editable report