Sessional Lecturer MHI2002H Emergent Topics in Health Informatics

University of Toronto; Toronto; On-site; CAD 60,000 - 80,000; Part time

Job summary

A leading educational institution in Toronto is seeking a Sessional Lecturer for a graduate course in Health Informatics. The successful candidate will have a PhD or Masters education and recent experience in health informatics, accompanied by teaching experience. Responsibilities include course design and assessment, ensuring accessibility to students outside of class hours. Salary is commensurate with experience. Application deadline is October 24, 2025.

Qualifications

• Recent experience in clinical and health informatics.
• Understanding of clinical work processes influenced by health informatics.
• Previous teaching experience at the graduate level.

Responsibilities

• Instruct a graduate course with competency-based methods.
• Design course content and assess student outcomes.

Skills

Clinical informatics knowledge

Teaching experience

Curriculum development

Familiarity with LMS tools

Education

PhD or Masters in health informatics

Job description

CUPE Local 3902 (Unit 3) Job Posting

Sessional Lecturer Position

Posting Date: October 3, 2025

Program: Master of Health Informatics (MHI)

Sessional Dates of Appointment: Winter 2026, January to April

Course Title: MHI2002H-S Emergent Topics in Health Informatics: Intelligent Medicine, Machine Learning and Knowledge Representation

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.

Qualifications:

• A PhD or Masters level education with recent experience in clinical and health informatics, preferably in the areas of ICT adoption, implementation, and evaluation;
• A robust understanding of clinical/clinician work processes, as influenced by health informatics and related technology;
• Past teaching experience related to health informatics, preferably at the graduate level;
• Prior experience in curriculum development and adult teaching-learning methods;
• 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).

Course Details:

• Class schedule: Weekly
• Estimated enrolment: 50
• Estimated TA support: based on enrolment - None

Duties:

• Course 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.

Salary and Application:

Salary: Commensurate with experience

How to submit an application: please send your CV and cover letter via e-mail to [e-mail].

Closing Date: October 24, 2025

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.

Note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.