Research Summer Student Ted Rogers Centre for Heart Research

Union: Non-Union 
Number of Vacancies: 1
New or Replacement: New
Site: Toronto Western Hospital
Department: Cardiology
Reports to: Dr. Mali Worme
Hours: 35 hours per week
Salary: $17.60 - $20.91 
Shifts: Monday to Friday
Status: Temporary Full-time
Closing Date: February 27 2026

Position Summary
This placement is for a summer student at either the undergraduate or medical student level with experience in programming coding and the application of artificial intelligence to medical imaging. The student will participate in research within the Echocardiography Laboratory at University Health Network by extracting echocardiographic studies and working with existing large image models in echocardiography to further develop algorithms that can differentiate between ischemic and non-ischemic cardiomyopathy. Using curated datasets from UHN representing specific non-ischemic cardiomyopathy subtypes (for example sarcoidosis amyloidosis Fabry disease arrhythmogenic right ventricular cardiomyopathy and iron overload cardiomyopathy etc ) the student will attempt to train existing echo models to differentiate etiologies of non-ischemic cardiomyopathy a significant clinical dilemma for cardiologists and heart failure specialists. 

Educational Objectives:

• To learn the basics of echocardiography nomenclature standard views and core image acquisition principles. 
• To expand skills in the use of large image models and related deep learning tools and to further develop their applications in echocardiography and cardiomyopathy phenotyping. 
• To work closely with the head of the Toronto General Hospital Echocardiography Laboratory and the labs Quality lead to gain exposure to Research methodology including Study design data curation and model evaluation. 

Proposed deliverables at the end of the placement: 

• Development and preliminary testing of a pilot large image modelbased algorithm aimed at differentiating ischemic from non-ischemic cardiomyopathy using echocardiographic data. 
• Exploratory analyses and models assessing the potential to distinguish between different etiologies of non-ischemic cardiomyopathy (for example sarcoidosis amyloidosis Fabry disease arrhythmogenic right ventricular cardiomyopathy and iron overload) based on echocardiographic features. 
• Preparation of an abstract and presentation summarizing the projects methods preliminary findings and future directions for submission to the Ted Rogers Centre for Heart Research Summer Research Day. 

Qualifications :

• Current undergraduate or medical student in a relevant field (for example: computer science engineering data science medicine or a related discipline).
• Demonstrated experience with Python and PyTorch for machine learning and deep learning projects. 
• Prior involvement in research projects that apply artificial intelligence to medical imaging modalities (for example: echocardiography cardiac MRI CT or other radiologic imaging). 
• Foundational understanding of medical AI development workflows including data preprocessing model training validation and basic performance evaluation. 
• Strong interest in cardiovascular medicine echocardiography and translational applications of AI in clinical care. 

Additional Information :

Why join UHN
In addition to working alongside some of the most talented and inspiring healthcare professionals in the world UHN offers a wide range of benefits programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor allowing you to find value where it matters most to you now and throughout your career at UHN.

• Competitive offer packages
• Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP access to Transit and UHN shuttle service
• A flexible work environment
• Opportunities for development and promotions within a large organization
• Additional perks (multiple corporate discounts including: travel restaurants parking phone plans auto insurance discounts on-site gyms etc.)

Current UHN employees must have successfully completed their probationary period have a good employee record along with satisfactory attendance in accordance with UHNs attendance management program to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading inaccurate or incorrect UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest however only those selected for further consideration will be contacted.

Remote Work :

No

Employment Type :

Contract