PhD Student - AI Research / Computer Vision Engineer – Medical Image Analysis

This project focuses on the development of AI-powered point-of-care ultrasound (POCUS) technology for early breast cancer detection. The aim is to enable accurate, operator-independent ultrasound-based assessment at the first point of contact by integrating advanced computer vision, deep learning, and explainable AI with low-cost handheld ultrasound devices.

The PhD candidate will primarily contribute to the AI and medical image analysis components of the project, working closely with engineers, data scientists, and clinicians to translate methodological advances into clinically robust solutions.

The PhD candidate will focus on AI development and computer vision research, including:

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  Developing deep learning models for ultrasound image enhancement, lesion detection, segmentation, and classification

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  Designing computer vision pipelines for ultrasound sweep analysis, including quality control and temporal modeling

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  Applying CNNs, transformer-based architectures, and self-/semi-supervised learning to breast ultrasound data

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  Integrating explainable AI (XAI) methods to improve interpretability and clinical trust

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  Working closely with clinicians and engineers to align AI development with clinical needs

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  Contributing to retrospective and prospective validation studies

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  Publishing research findings in peer-reviewed journals and presenting at international conferences

The position is hosted within the Image-Guided Surgery group at NKI, which has a strong track record in medical image analysis, tissue sensing, AI-assisted diagnostics and treatment, and translational MedTech research. The research group is a large multidisciplinary team (~30 members), including medical imaging scientists, biophotonics researchers, AI researchers, physicians, technical physicians, surgeons, radiologists, software developers, and biomedical engineers. Clinical validation and data collection are carried out in collaboration with clinicians at NKI, providing a unique setting for clinically driven AI research with direct patient impact.