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Flemish BrabantOn site38 hours/week>12months
A research institution is seeking a researcher for a project focused on translational cell and tissue research, embedded within an Imaging and Pathology department. The team works at the interface of cancer biology, medical imaging, and artificial intelligence. The researcher will join an international consortium and collaborate closely with computational and clinical researchers.
What you will do.
- Lead the development, fine-tuning, and benchmarking of foundation models for breast radiology, including mammography, magnetic resonance imaging, and ultrasound.
- Develop robust lesion-, image-, and patient-level representations that capture characteristics relevant to invasive lobular carcinoma while accounting for variation between institutions, scanner vendors, and acquisition protocols.
- Integrate radiology representations with embeddings derived from digital pathology images and contribute to multimodal models for diagnosis, staging, prognosis, relapse prediction, and treatment-response modelling.
- Design and perform rigorous internal and external validation, including cross-site benchmarking, uncertainty estimation, model calibration, and subgroup analyses.
- Develop reproducible and well-documented software, maintain data-analysis pipelines, and contribute to model documentation and responsible research practices.
- Collaborate closely with radiologists, pathologists, computational scientists, and clinical researchers across an international consortium.
- Communicate results through scientific publications, presentations, and consortium activities.
- Potentially supervise doctoral and master’s students and contribute to the scientific coordination of related research activities.
Profile
- Motivated and independent researcher with a strong computational background and demonstrated experience in radiology image analysis.
- PhD in computer science, artificial intelligence, biomedical engineering, medical imaging, bioinformatics, statistics, or a closely related computational field.
- Strong programming skills, preferably in Python, and substantial experience with machine learning or deep learning for medical images.
- Scientific publication record appropriate to your career stage.
- Proven research experience in radiology image analysis is required.
- Experience with DICOM and one or more breast-imaging modalities (mammography, ultrasound, MRI) is strongly preferred.
- Experience with digital pathology, multimodal learning, three-dimensional computer vision, self-supervised learning, foundation models, model calibration, or high-performance computing is an advantage.
- Able to take intellectual and technical ownership of an ambitious research project while collaborating effectively in an interdisciplinary and international team.
- Work in a structured and reproducible manner and communicate scientific results clearly in English, both orally and in writing.
- Interested in clinically meaningful artificial intelligence and motivated to work closely with radiologists, pathologists, and other clinical and computational researchers.
Practical
- The position provides access to unique multi-site breast cancer datasets and the computational infrastructure required to analyze large collections of medical images.
- You will be supervised by experts in breast radiology, digital pathology, biomedical AI, and translational cancer research.
- The position offers opportunities to publish in peer-reviewed scientific journals, present at international conferences, supervise junior researchers, initiate new collaborations, and further develop your independent academic profile.
How to apply
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