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 - $4,998.74Sessional Lecturer I - Long Term - $5,349.61Sessional Lecturer II - $5,349.61Sessional Lecturer II - Long Term - $5,476.98Sessional Lecturer III - $5,476.98Sessional 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,
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