University Health Network
Healthcare
FacultyAIScientist(ScientistII)
Neural analysis suggests this role is
optimal for mid candidates.
“Faculty AI Scientist (Scientist II) at University Health Network. Skills: Cardiovascular Artificial Intelligence, AI model development and deployment, Python, Machine Learning, Deep Learning. Lead the development, validation, and deployment of AI models for cardiovascular applications using multimodal data. Apply the latest approaches in AI. Work closely with clinicians to identify high-value problems and translate them into AI solutions. Assemble a cross-functional team for end-to-end AI initia”
What You'll Achieve.
Improve the management of patients with conditions that can lead to heart failure. Improve diagnosis, risk prediction, clinical decision-making, workflow, and patient outcomes across cardiovascular care. Ensure that AI tools are safe, auditable, scalable, and aligned with strategic objectives. Improve patient outcomes.
Industry & Context.
identify high-value problems; translate them into ethical, scalable AI solutions
A PMCC appointment is expected at the rank of Scientist, on a career path to Senior Scientist over a six-year period (tenure-track-equivalent). Criminal Record Check may be required.
What They're Looking For.
Must Have
A PhD or equivalent advanced degree in computer science, machine learning, biomedical engineering, data science, statistics, or a related field. Expertise in modern AI and machine learning methods, with hands-on experience developing state-of-the-art models. Programming skills, especially in Python, and experience with modern ML frameworks and compute environments. Demonstrated success in research, including peer-reviewed publications and/or impactful applied AI work, as well as a track record of peer-reviewed funding. Ability to work effectively in interdisciplinary teams and communicate complex ideas clearly to both technical and clinical audiences.
Nice to Have
Previous work in cardiovascular medicine, biomedical data science, or healthcare AI preferred. Multimodal data fusion, medical imaging, time-series analysis, NLP, or foundation model development preferred. Real-world deployment of AI in healthcare settings preferred. AI safety, explainability, fairness, governance, and model monitoring preferred.
What You'll Do.
Lead the development, validation, and deployment of AI models for cardiovascular applications using multimodal data.
Apply the latest approaches in AI.
Work closely with clinicians to identify high-value problems and translate them into AI solutions.
Assemble a cross-functional team for end-to-end AI initiative delivery.
Build reproducible pipelines for data curation, model training, evaluation, monitoring, and continuous improvement.
Support prospective validation, clinical integration, and post-deployment monitoring.
Lead publications, grants, and presentations.
Supervise trainees and collaborate across scientific, clinical, and industry partnerships.
How You'll Work.
Team & Collaboration
Join the highly collaborative and exceptionally productive PMCC AI team, which brings together clinicians, AI and data scientists, software developers, machine learning engineers, researchers, and operational leaders. Collaborate across scientific, clinical, and industry partnerships.
Communication Scope
communicate complex ideas clearly to both technical and clinical audiences
Process & Methodology
Lead the development, validation, and deployment of AI models, Assemble a dedicated, cross-functional team, Build reproducible pipelines
Full Job Description
UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. With 10 sites and more than 44,000 TeamUHN members, UHN consists of Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, The Michener Institute of Education and West Park Healthcare Centre. As Canada's top research hospital, the scope of biomedical research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. UHN has the largest hospital-based research program in Canada, with major research in neurosciences, cardiology, transplantation, oncology, surgical innovation, infectious diseases, genomic medicine and rehabilitation medicine. UHN is a research hospital affiliated with the University of Toronto. UHN’s vision is to build A Healthier World and it’s only because of the talented and dedicated people who work here that we are continually bringing that vision closer to reality. [www.uhn.ca](https://www.uhn.ca/) Union: Non-Union Number of vacancies: 1 New or Replacement Position: New Site: Toronto General Hospital Department: Peter Munk Cardiac Centre Reports to: PMCC Research Director, and Executive Lead, PMCC AI Team Hours: 37.5 hours per week Shifts: Days Status: Permanent Full-Time Closing Date: June 24, 2026 Position Summary The PMCC (Peter Munk Cardiac Centre) at University Health Network (UHN), which includes a research institute affiliated with the University of Toronto, seeks a faculty Scientist for a full-time appointment at the Assistant or Associate Professor level, to establish an independent world-class research program in Cardiovascular Artificial Intelligence. The successful candidate will be supported by a generous start-up package, an independent, modern laboratory space, and assistance in obtaining a cross-appointment to the Department of Computer Science at the University of Toronto. A PMCC appointment is expected at the rank of Scientist, on
Applying for this Faculty AI Scientist (Scientist II) role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on SmartRecruiters
- SmartRecruiters often includes a video screening step — check camera and mic permissions.
- Link your GitHub or portfolio directly in the profile section for technical roles.
- Applications may be reviewed by AI scoring before reaching a recruiter — use keywords from the job description.
ANONYMOUS · UNFILTERED
What do employees actually say about University Health Network?
Real rants from real employees. Read before you apply.