Date Posted: 10/24/2026
Closing Date: 11/13/2026, 11:59PM EDT
Req ID: 50753
Job Category: Sessional Instruction
Faculty/Division: Temerty Faculty of Medicine
Department: Dept of Lab. Medicine & Pathobiology
Campus: St. George (Downtown Toronto)
Description:
This course is intended for graduate students in Health Sciences to learn the basic principles of machine learning in biomedical research and to build and strengthen their computational skills of medical research. The course aims to equip students with the fundamental knowledge of machine learning (ML).
During the course, students will acquire basic computational skills and hands-on experience to deploy ML algorithms using python. Students are expected to be familiar in python prior to taking this course.
Students will learn the current practices and applications of ML in medicine and understand what ML can and cannot do for medicine. The goal of this course to establish an essential foundation for graduate students to take the first steps in computational research in medicine.
Number of available positions: 1 postion x 0.25 FCE (co-teaching course)
Estimated course enrollment: ~ 30 students
Estimated TA support: not applicable
Class schedule: Wednesays from 11:00 AM – 1:00 PM
Sessional dates of appointment: January 1, 2027 – April 30, 2027
Salary (0.25 FCE - course will be co-taught):
Sessional Lecturer I - $4,998.74 Sessional Lecturer I - Long Term - $5,349.61 Sessional Lecturer II - $5,349.61 Sessional Lecturer II - Long Term - $5,476.98 Sessional Lecturer III - $5,476.98 Sessional Lecturer III - Long Term - $5,614.45
Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.
Minimum qualifications: PhD in computer science or in a health science discipline with a strong background in machine learning and its application in biomedical research. Programming skills in Python are required for the assignments. Also required is the demonstration of leadership in curating technical material to present to an audience as demonstrated by the organization of research workshops.
Preferred qualifications: Extensive research experience with published research papers applying ML in biomedical research is strongly preferred. Experience creating and maintaining a website that highlights the course requirements, announcements and grade breakdown
Description of duties: Preparation and delivery of course content, including lectures and/or seminars; creation of courseware; the development and administration of assignments, tests and examinations; marking and grading of student work and the submission of grades to appropriate University officials, maintenance of reasonable hours of student contact outside of scheduled contact hours. Creation, maintenance and management of the Quercus site for the course, collecting material from the lecturers in advance and posting lecturer slide sets (power points), handouts, reading lists, journal articles and bibliographies and preparing other course content as required.
Application instructions: Please submit application using the following form: Winter 2027: Sessional Lecturer: LMP1210H: Basic principles of machine learning in biomedical research (0.5 FCE)
CAUTION: This ad is “posted only” to the U of T CUPE 3902 Unit 3 job board. Please see the informationdirectly above for the application instructions; applications submitted via the "Apply Now" button on this page will NOT be considered for this position.
This job is posted in accordance with the 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. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement. Please 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.
