Postdoctoral Research Fellow in Cardiovascular Imaging, Precision Health and Artificial Intelligence (MOSAIC study)
Confirmed on the employer's own hiring board on Sep 24, 2026. First seen by Alion on Sep 23, 2026.
Job Category
Faculty Non BargainingJob Title
Postdoctoral Research Fellow in Cardiovascular Imaging, Precision Health and Artificial Intelligence (MOSAIC study)Department
Tsang Laboratory Division of Cardiology | Department of Medicine | Faculty of Medicine (Teresa Tsang)Posting End Date
October 7, 2026Note: Applications will be accepted until 11:59 PM on the Posting End Date.
Job End Date
October 31, 2027Note: The expected salary for this position is $100,000/year. Salary will be commensurate with qualifications and experience.
The desired start date is as early as November 1, 2026 no later than December 1, 2026.
The position is full-time for one year with the possibility of extension subject to work performance, funding availability and compliance with UBC policies.
At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career.
Job Summary
The Division of Cardiology in the Department of Medicine at the University of British Columbia, Vancouver Campus, is seeking a passionate and collaborative postdoctoral fellow to join Dr. Teresa Tsang’s team in advancing cardiac precision medicine through artificial intelligence and machine learning. The postdoctoral fellow will contribute to the development of a comprehensive, multi-modal framework for predicting and managing cardiovascular disease by integrating genomic and -omic data, echocardiographic imaging, and clinical information. This position will support the Multi-Omics and Sonography to Advance Integrated Cardiac Care MOSAIC Study, a newly funded, multi-site provincial initiative that will advance our understanding of how genetic factors influence cardiac structure and function, and yield AI models that link phenotypic findings with genetic data to predict CVD risk and disease progression. As personalized therapies and AI-driven point-of-care tools become increasingly vital, this work plays a key role in promoting equitable access to care and expert interpretation of ultrasound imaging.
Research Focus and Work Performed:
- Develop AI models that connect echo findings with genomic data to predict cardiovascular risk and disease progression in diverse populations.
- Perform AI/ML analyses on echo images, standardize protocols, and integrate AI tools with clinical insights.
- Perform quality control and validate AI outputs to enhance the reliability and scalability of the study outcomes
- Ensure clinically relevant results are aligned with study objectives.
- Work directly with academic and industry collaborators to translate research findings into tools that improve patient care and population health.
- Research and scholarly Leadership: Design and execute original research projects with rigorous methodology. Lead or co-lead grant proposals and manuscript preparation (including first- or senior-author publications). Present findings at conferences and contribute to multi-investigator projects, white papers, reports, book chapters, and other publications.
- Training and Mentorship: Co-supervise students and research assistants with structured feedback on study design, analysis, and writing. Model responsible conduct of research and mentorship best practices.
- Research program and compliance leadership: Manage research operations, workplans, and timelines. Ensure compliance with institutional review, privacy, and data-use requirements. Implement robust data management, version control, and reproducibility practices. Maintain data security and governance standards.
- Collaboration and impact: Build interdisciplinary partnerships across academic, clinical, industry, and community organizations. Co-develop shared resources and contribute to standards development and open science initiatives.
- Academic presence and dissemination: Present work locally, nationally and internationally through conferences, seminars, and workshops. Translate findings for diverse audiences while maintaining scientific rigor.
Qualifications:
- PhD in artificial intelligence, machine learning, cardiovascular medicine, genomics, or a related discipline, obtained within the last 5 years, by the time of the appointment start date.
- Demonstrated expertise in current machine learning techniques applied to biological, imaging, or clinical data.
- Proficiency in ML frameworks (experience with LLavaMed, EchoPrime and DNABERT considered an asset) and programming languages such as Python or R.
- Experience working with medical imaging or genomic datasets is an asset.
- Excellent communication skills and a demonstrated ability to work effectively in interdisciplinary teams.
- Ability to adapt and navigate complex health systems and evolving health trends
- Strong conceptual, analytical, and critical thinking abilities
- Willingness to respect diverse perspectives, including perspectives in conflict with one’s own.
- Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion.
Opportunities and Environment:
- Collaborate with leading academic institutions and partners at the intersection of AI and personalized medicine.
- Publish high-impact research and drive healthcare advances with clear translational potential.
- Advance access to expert interpretation of imaging data at scale through AI/ML applications.
- Help shape a future where AI models support population-wide, equitable delivery of cardiovascular care.
The UBC Department of Medicine fosters a supportive, collaborative, and inclusive research environment. Postdoctoral fellows benefit from structured mentorship and career development opportunities tailored to diverse career goals and lived experiences.
How to Apply:
To apply, please submit a single PDF containing:
- Cover letter (2 pages max) describing your research interests and fit for the role
- Curriculum vitae including publication list
- Names and contact information for 3 references
- Review of applications will begin immediately and continue until the position is filled.
- For any inquiries regarding this position, please contact Dr. Teresa Tsang ([email protected])