Post-doctoral Fellowship in Machine Learning

St. Paul’s Hospital and University of British Columbia, Vancouver, Canada

PDF in Machine Learning for Image Analysis in Lung Disease


A post-doctoral position with one-year term and extendable for another year with satisfactory progress is available immediately for a highly motivated recent PhD graduate to join an interdisciplinary collaborative research team at the UBC Center for Heart Lung Innovation (HLI) at St. Paul’s Hospital, which offers a world-class research environment and career development opportunities.

The research will focus on the development and application of machine learning methods to the analysis of computed tomography (CT) and histopathological images of the lung to enhance the biological understanding of chronic obstructive pulmonary disease (COPD) and associated diseases. The methodological focus will be the integration of multi-modal data including imagery for optimized predictions of clinical outcomes. The position is highly suitable for those pursuing a research career in advanced data analytics in academic or industry, particularly in the life sciences, but also in other application domains.

The research fellow will be co-supervised by Dr. James Hogg (MD, PhD, Emeritus Professor and Senior Investigator at the HLI) and Dr. Don Sin (MD, MPH, Professor and Director of the HLI), both world-renowned experts in COPD and associated lung diseases, and Dr. Roger Tam (PhD, Associate Professor in the Department of Radiology and School of Biomedical Engineering), a computer scientist with expertise in machine learning in medical image analysis. In addition, the HLI and UBC offer a vast network of clinical and technical experts for consultation and learning.


Highly motivated individuals with a recent (within 5 years) PhD in computer science, biomedical engineering, or related field, excellent academic credentials, and publications in high impact conferences and journals are encouraged to apply. Demonstrated familiarity with a range of machine learning methods, including ensemble learning methods such as random forests and feature learning methods such as deep learning, and expertise in the application of such methods to image analysis are required. Experience with biomedical imaging data is preferred. UBC hires on the basis of merit and is committed to employment equity. We encourage all qualified persons to apply. However, all else being equal, Canadian citizens and permanent residents will be given priority.

Duration: 1 year with possible extension for a second year.

How to Apply:

Please submit a cover letter, curriculum vitae, and the names and full contact information for three professional references. The cover letter should include a description of your previous research experience and long-term career goals. Send electronic applications by June 30, 2019 to

Apply by June 30, 2019