College of Community & Global Health

Rady Faculty of Health Sciences

Job details:

Course: Advanced Topics in Community Health I: Applied Machine Learning for Health Data CHSC 7400 T02 - 3 Credit Hours

Start date

January 1, 2027

End date

April 30, 2027

Work schedule

Expected total hours

Appointment Pay Rate

$6,654.00

For more information please contact: Erin Langford - [email protected]

Key responsibilities:

- Preparing instructional and testing materials relevant to the course being taught.
- Instructing/teaching/testing.
- Marking/grading of exams and assignments etc.
- Providing constructive feedback to students.
- Maintaining regular office hours.

Applications may be considered after the posting closing date. If more than one section is advertised for this course different applicants may be considered for each section, and applicants are required to indicate their preferred section.

Where a University of Manitoba student is the successful candidate, the terms and conditions of employment, including remuneration, will be governed by the UM/CUPE 3909 (Student) Collective Agreement.

Qualifications:

- Master's degree, Ph.D. or Ph.D. candidate preferred.
- Excellent communication skills, both oral and written, in the English language is required.
- Background/specialization in subject area required.
- Demonstrated competence in post-secondary teaching required.
- Empathetic approach to the instructional needs and concerns of students is required.
- Previous teaching in the subject area or related area would be an asset.

Additional information:

Tuesdays 1:30pm - 4:20pm This course will provide an introduction to machine learning methods for students who are interested in modeling and prediction using health data.



Both supervised and unsupervised machine learning methods for structured health data will be examined. Some natural language process methods will be explored.

Steps in the machine learning pipeline, including data pre-processing and preparation, model specification and evaluation, and data visualization, will be covered. Students who participate in this course will explore diverse types of population and public health data in their applications of machine learning methods.

Classes in this course may consist of:

- Discussions of assigned reading materials.
- Skill-building activities around data management, analyses and visualization of datasets, and communicating about one's research to both academic and non-academic audiences, primarily using R software.

The University of Manitoba is committed to the principles of equity, diversity & inclusion and to promoting opportunities in hiring, promotion and tenure (where applicable) for systemically marginalized groups who have been excluded from full participation at the University and the larger community including Indigenous Peoples, women, racialized persons, persons with disabilities and those who identify as 2SLGBTQIA+ (Two Spirit, lesbian, gay, bisexual, trans, questioning, intersex, asexual and other diverse sexual identities). If you require accommodation supports during the recruitment process, please contact [email protected] or (phone hidden). Please note this contact information is for accommodation reasons only.

Application materials, including letters of reference, will be handled in accordance with the protection of privacy provisions of "The Freedom of Information and Protection of Privacy Act" (Manitoba). Please note that curriculum vitae will be provided to participating members of the search process.

📌 Instructor - CHSC 7400CUPE Sessional (Winnipeg)
🏢 University of Manitoba
📍 Winnipeg