Careers at UHN

Job Description

Artificial Intelligence Scientist - UHN/Peter Munk Cardiac Centre - Toronto, Ontario

JOB POSTING # 817294

Position:         Artificial Intelligence Scientist - UHN / Peter Munk Cardiac Centre
Department:   Peter Munk Cardiac Centre, Techna Institute for the Advancement of Technology for Health
Reports To:     Program Medical Director, Peter Munk Cardiac Centre; Research Director, Vector Institute; and Institute Director, Techna, UHN
Site:               Peter Munk Cardiac Centre, Toronto General and other UHN hospital sites as needed; and Vector Institute, Mars Centre, West Tower, Suite 710
Status:           Permanent Full-Time
Salary:           Extremely attractive packaging, commensurate with academic and professional experience related to the position


The PMCC is recognized as a global leader in the management of diseases of the heart and blood vessels. First established in 1993, the PMCC aims to be a pioneer in integrative, digitally-enabled strategies for the prevention, treatment and support of those suffering from cardiovascular disease. To accomplish this goal, we are creating a globally-unique ecosystem that attracts the best talent from diverse fields, including cardiovascular imaging, medicine and surgery, computer science, engineering and healthcare economics. This ecosystem will promote excellence in patient care, and will drive high impact basic science and education research.

The recently announced Phase IV of the PMCC envisions our evolution over the next ten years. We will shape the future of cardiovascular care through transformative digital technology, predictive analytics, precision genomic medicine, innovation, the generation of new knowledge, and quality assurance that will continue to enable outstanding patient experiences. 

The PMCC is part of the University Health Network.


We are seeking a creative data scientist to be the PMCC Artificial Intelligence (AI) Team Lead, who will develop novel machine learning approaches and integrate them into the management of patients with heart and vascular disease.

The appointed candidate will initiate and drive a unique, dedicated partnership between the PMCC, University Health Network’s (UHN) Digital Operations and the Vector Institute for artificial intelligence. The PMCC AI Team will influence development of the Digital Cardiovascular Health Platform (DCHP), which includes a data lake that integrates blood tests, clinical notes, X-rays, ultrasounds, CT and MRI scans, pathology slides, and genetic information from the 163,000 patients seen per year in the PMCC, as well as information contained in provincial-level healthcare databases. The PMCC AI Team will integrate machine learning into the PMCC, develop predictive models and decision support that will tailor the care of patients to their unique clinical and genomic traits, and improve the efficiency of healthcare delivery, clinical outcomes, and patient satisfaction.

The candidate will be a Vector Faculty Member on a part-time basis for an indefinite duration, will maintain departmental and graduate school faculty status at the University of Toronto (U of T), and will have the freedom to pursue independent machine learning-based research initiatives.


The PMCC AI Team Lead will have an exciting opportunity to create and apply machine learning knowledge at the PMCC that enables sustainable innovation to support predictive analysis and precision medicine, enable the next generation of analytics through high performance computing, deep learning platforms, and real-time data processing and decision support, and contribute to the PMCC becoming the world’s premier cardiovascular centre. This will be accomplished through direct collaboration with PMCC physicians and surgeons, who will work with the PMCC AI Team to identify and manage cardiovascular health care problems that are amenable to machine learning solutions.

With access to rich and complex cardiovascular care and research data sets that will be of interest to the broader machine learning research community, the Lead will create first-of-its-kind machine learning systems to incorporate new data and new features that will be scalable to other clinical domains at UHN, and will determine mechanisms necessary to unlock the value of data generated during the course of treatment.

The Lead will be uniquely positioned to inform and champion the use of modern machine learning techniques at the PMCC that contribute meaningfully to its scientific research and algorithm development activities, support the creation of high quality expository and research publications on the use of machine learning in cardiovascular care, and enable a pivot to a learning health system that drives future PMCC research initiatives.

In addition, the Lead will have a powerful platform to encourage researchers in the field of machine learning to address problem areas that are of interest to the PMCC and UHN; assess new results from the field of machine learning for efficacy and for relevance to the PMCC’s efforts, and leverage machine learning and industry partnerships to provide focus on the intersection of machine learning and cardiovascular healthcare delivery and research.


Machine Learning and AI Research

• Facilitate the invention of new machine learning tools, the incorporation of cutting-edge computer science scholarship, and the application of machine learning techniques in cardiovascular care, research and clinical operations;
• Create a customizable framework to apply machine learning to data captured in provincial-level healthcare databases, and in the PMCC’s Digital Cardiovascular Health Platform, which is stored in UHN Digital’s systems for further analysis and learning;
• Collaborate with the U of T to identify and create opportunities for students to learn in a collaborative machine learning-rich environment;
• Pursue machine learning-based research initiatives in collaboration with colleagues at the Vector Institute, Techna and the U of T; and
• Promote and maintain Canadian excellence in deep learning and machine learning, and actively seek ways to enable and sustain AI-based economic growth in Canada

Leadership and Operations

• Establish and lead a Team of 8-10 individuals (including data scientists, software engineers and graduate students) that is focused on the delivery and optimization of cardiovascular patient care and related research;
• Ensure that the Team coordinates and applies machine learning approaches, including object recognition, natural language processing, and machine learning methods to the PMCC’s comprehensive and evolving data science needs;
• Co-chair the PMCC AI Council - which will bring together data scientists with PMCC physicians and surgeons - with the PMCC Program Medical Director. The PMCC AI Council will identify PMCC clinical and research issues that could be addressed though machine learning-based approaches, support the use of machine learning techniques, and organize topical meetings on the applications of machine learning in cardiovascular care and research;
• Develop ideas for commercialization, and patent and productize relevant applications of machine learning that lead to the creation of new intellectual property;
• In collaboration with the PMCC Medical Director, manage the annual PMCC AI Team operating budget, promote collaboration with the private sector and other partners, and investigate, pursue and secure revenue sources required to make the PMCC AI Team self-sufficient; and
• Contribute substantially to organizational infrastructure by participating in the ongoing fulfillment and/or formulation of the mission, strategic direction, operating plan, and goals of the PMCC, Techna, in collaboration with the Directors of the PMCC and Techna and Vector


• A Ph.D. in Computer Science or an advanced degree in a similar field, and a minimum of 2 years of related experience, or a combination of education, experience and demonstrated ability that is recognized internally and externally as equivalent;
• Expertise in machine learning, including but not limited to deep, unsupervised, and reinforcement learning, optimization, theory; and one or more areas related to applied machine learning, including but not limited to health, medicine, biology, technology development, vision, robotics, and natural language processing;
• Lead a high-performing team of experts and successfully deliver strategic value and measureable results;
• Demonstrated experience in the application of machine learning to a practical domain, and the development of organizational AI/data systems;
• Preferably have published in top-notch peer-reviewed journals; and
• Healthcare experience preferred, but not necessary


• Cover letter;
• Curriculum Vitae;
• A research statement;
• Links to at least three recent and related publications; and
• At least three letters of recommendation


UHN consists of Toronto General and Toronto Western Hospitals, the Princess Margaret Cancer Centre, Toronto Rehabilitation Institute, and The Michener Institute of Education. The scope of research and complexity of cases at UHN has made it a national and international source for discovery, education and patient care.

UHN has the largest hospital-based research program in Canada, and a proud history of innovative research and important discoveries. Researchers at UHN are focused on investigating the causes of numerous diseases, and are developing new and better ways to treat them and deliver better care. Disease area research includes cancer, cardiology, transplantation, immunology, infectious disease, health services, rehabilitation, fitness and mobility, neural and visual sciences, musculoskeletal disease and community and population health. UHN has five research institutes - Princess Margaret Research Institute, TECHNA Institute, Toronto General Hospital Research Institute, Toronto Rehabilitation Institute, and Krembil Research Institute.

The Vector Institute will work with academic institutions, industry, start-ups, incubators and accelerators to advance AI research and drive the application, adoption and commercialization of AI technologies across Canada. Vector strives to attract the best global talent focused on research excellence in deep learning and machine learning. Our researchers and academic partners will be part of a vibrant community of innovative problem-solvers, working across disciplines on both curiosity-driven and applied research.

POSTING DATE: January 19, 2018      POSTING DEADLINE: Until filled

For current UHN employees, only those who have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, and possess all the required experience and qualifications should apply.

The University Health Network, Vector Institute and the University of Toronto are committed to championing accessibility, diversity and equal opportunity, and especially welcome applications from racialized persons/persons of colour, women, Indigenous/ Aboriginal People of North America, persons with disabilities, LGBTQ persons, and others who may contribute to the further diversification of ideas.

Requests for accommodation can be made at any stage of the recruitment process, providing the applicant has met the bona-fide requirements for the open position. Applicants need to make their requirements known when contacted.

All qualified candidates are encouraged to apply; however, Canadians and Permanent Residents will be given priority. While we thank all applicants, only those selected for an interview will be contacted.

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