Sessional Lecturer- MHIEmergent Topics in Health Informatics

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Posting Date:
September 21, 2026

Program:
Masters of Health Informatics (MHI)

Sessional Dates of Appointment:
Winter 2027, January
- April Existing Vacancy:
Yes

Course

Description:

This course is designed for students to understand the issues associated with the use of data management technology and analytics solutions in the healthcare system. This includes systems and technologies used to generate, harvest and store clinical data and methods used to create predictive models (including but not limited to methods associated with machine learning). Furthermore, issues related to delivery of predictive analytics and implementation of algorithms in care settings along with clinical, business and ethical challenges will be explored.

In addition, an overview of the issues within the health industry that are driving the use of data, will be reviewed, including population health management, clinical decision support, and advanced research. The goal is for students to be able to gain experience in the description, architecture and implementation planning of data infrastructure in the healthcare system along with providing a strong foundation in regard to analytics lifecycle and methods.

Objectives:

Students will enhance abilities to:

Describe and conceptualize data infrastructure used in the healthcare system, including classical and non-classical sources of data and the technologies and methods used to harvest and store clinical data.

Utilize statistical and machine learning tools to create and validate predictive models and present analytics results using visualization tools.

Identify and problem-solve the organizational, clinical and ethical implementation challenges associated with predictive algorithms in healthcare.

Gain the ability to position data management and advanced analytics in the context of health system challenges and business models.

Class schedule:
Weekly sessions from 1:10pm–4pm on Fridays, between Jan 15 and March 12, 2027.

Delivery mode:
In-person

Qualifications:

• A PhD or Masters level education with recent experience in clinical and health informatics, preferably in the areas of AI, ML, design, modeling, implementation and policy ;
• A robust understanding of clinical/clinician work processes, as influenced by health informatics and AI and ML technologies.
• P ast teaching experience related to health informatics, preferably at the graduate level;
• Comfortable with electronic teaching tools such as Learning Management Systems (e.g., Blackboard), PowerPoint, as well as on-line collaboration tools (Blogs, Wikkis , Discussion Boards, Webinars, or Video-conferencing ).

Duties:

Course co- instructor for a professional graduate course using competency-based learning and assessment methods.

Responsible for course design and assessment of student outcomes. Must be accessible to students outside of classroom hours.

Please note that should rates stipulated in the collective agreement vary from ratesstatedin this posting,the ratesstatedin the collective agreement shall prevail.

Closing Date:
October 12, 2026

This job is postedin accordance withthe CUPE 3902 Unit 3 Collective Agreement.

It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Preferenceinhiringisgiventoqualifiedindividualsadvancedto therankof

Sessional

Lecturer II orSessional

Lecturer IIIinaccordancewith Article
14:12oftheCUPE
3902

Unit3collectiveagreement.

Please note:

Undergraduateorgraduatestudentsandpostdoctoralfellowsofthe Universityof Torontoarecoveredby  theCUPE
3902

Unit1collectiveagreementrather thanthe

Unit3collectiveagreement,andshouldnotapplyforpositionspostedunderthe

Unit3collectiveagreement.

Diversity Statement

The University of Toronto embraces Diversity and is building aculture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples,Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities.

We value applicants who have…