Postdoc: Multimodal Breast Imaging AI & Pathology

KU Leuven; Vlaams-Brabant; Sur place; EUR 60 000 - 80 000; Plein temps

Avantages offerts par ce poste

Publish in journals

Present at conferences

Supervise researchers

International collaboration

Résumé du poste

KU Leuven's Laboratory for Translational Cell and Tissue Research invites applications for a full-time postdoctoral position in breast-imaging AI as part of the M4GIC-ILC consortium. The candidate will lead foundation-model adaptation and multimodal integration of radiology and digital pathology.

We offer a three-year contract with a preferred start of 1 October 2026, access to multi-site breast cancer datasets, and opportunities to publish, present at conferences, and supervise junior

Qualifications

• PhD in a relevant computational field with strong publication record.
• Strong programming skills, preferably Python.
• Substantial experience with machine learning or deep learning for medical images.
• Proven experience in radiology image analysis and familiarity with DICOM.
• Experience with digital pathology, multimodal learning and foundation models is advantageous.

Responsabilités

• Lead development, fine-tuning, and benchmarking of foundation models for breast radiology.
• Develop lesion-, image-, and patient-level representations across imaging modalities.
• Integrate radiology embeddings with digital pathology features for multimodal models.
• Perform rigorous validation, cross-site benchmarking, and model calibration.
• Develop reproducible software and data-analysis pipelines; document methods.

Connaissances

Python programming

ML/DL for medical images

Radiology image analysis

English communication

Formation

PhD in computer science, AI, biomedical engineering, medical imaging, bioinformatics, statistics or related

Outils

DICOM

High-performance computing

Description du poste

KU Leuven's Laboratory for Translational Cell and Tissue Research invites applications for a full-time postdoctoral position in breast-imaging AI as part of the M4GIC-ILC consortium. The candidate will lead foundation-model adaptation and multimodal integration of radiology and digital pathology.

We offer a three-year contract with a preferred start of 1 October 2026, access to multi-site breast cancer datasets, and opportunities to publish, present at conferences, and supervise junior