Join Our Team

We invite you to explore joining our lab as a postdoctoral fellow or graduate student to carry out world-class research in the area of multi-modal medical image analysis (focusing on machine and deep learning) for health applications (e.g., cancer diagnosis and treatment). 

The successful candidates will complement a collaborative team of scientists, graduate students, and other postdocs in Vancouver, Canada, in the areas of oncology, genomics, image-guided interventions, and medical image reconstruction and analysis. 

The trainees will join SFU's School of Computing Science, ranked one of the top 50 CS schools worldwide and #1 in Canada in computer vision and graphics, have the opportunity to work closely with the BC Cancer Agency, BC Cancer Foundation, Vancouver General Hospital, and other UBC biologists and clinicians.   

Students will have access to advanced computing infrastructure and have the opportunity to enrol in courses across different universities via the Western Deans Agreement.  All this while enjoying the  safe, friendly and scenic city of Vancouver with its multicultural population, outdoor-focused culture, and diverse culinary scene.  

Postdoctoral candidates are expected to have published, as a first-author, in top venues (MedIA, IEEE TMI, MICCAI, IPMI, ICCV, CVPR, ECCV, NeurIPS, ICLR, ISBI, SPIE MI, MIDL, or similar) during the past few years. Experience in 3D medical image processing, segmentation, registration, (deep) machine learning, graphical models, and optimization is important, as well as excellent programming skills (e.g., Python, C/C++, MATLAB) and scientific writing and communications abilities.

Ideal PhD students are those who hold BSc and/or MSc degree(s) (direct entry from BSc to PhD is possible for exceptional candidates) in computer science, electrical or computer engineering, applied mathematics or similar disciplines, have completed their MSc thesis or BSc thesis/project in image processing, computer vision, machine learning, and/or optimization topics (or have strong interests in these topics and their applications in medicine), have excellent programming skills (e.g., Python, C/C++, MATLAB), and excellent written and spoken English.