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Sessional Lecturer, INF2258H – Explainability & Fairness for Responsible Machine Learning Jobs in Greater St. George Area at University of Toronto – Woodsworth College
Title: Sessional Lecturer, INF2258H – Explainability & Fairness for Responsible Machine Learning
Company: University of Toronto – Woodsworth College
Location: Greater St. George Area
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Sessional Lecturer, INF2258H – Explainability & Fairness for Responsible Machine Learning
University of Toronto
Faculty of Information
Sessional Lecturer
Fall Term 2026 (September – December)
INF2258H – Explainability & Fairness for Responsible Machine Learning
Course Description
( Previously listed as INF2404H ) Machine Learning applications are increasingly utilized to make crucial decisions in many sectors of our economy and society. These include, but are not limited to, healthcare, financial services, public safety, and higher education. Predictions from machine learning systems are incorporated within organizational processes to support evidence-based decision-making. This course examines state of the art techniques and technologies related to explainability and fairness in machine learning applications, including generative AI. These human-centric aspects play a significant role in the design and operation of machine learning applications. Absence of explainability and fairness capabilities in a machine learning application erodes its public legitimacy and undermines its social licence. This reduces its acceptance and adoption in the real-world. Students will use frameworks and techniques for architectural modeling, analysis, and design to understand explainability and fairness in the context of machine learning applications.
This course can be used to fulfil the “Professional Values” Requirement.
Estimate of the course enrolment: 35
Estimate of TA Support: None anticipated. Estimate of 75 hours with enrollment of 36 or greater. Allocation of TA hours, if any, will be based on enrolment numbers.
Class Schedule: TBD. You are required to be located in geographical proximity to the applicable University premises in order to attend and perform your duties on University premises as of the Starting Date.
Sessional dates of appointment: September 1, 2026 – Desember 31, 2026
Salary
Sessional Lecturer I: $10,889
Sessional Lecturer I Long Term: $11,652
Sessional Lecturer II $11,652
Sessional Lecturer II Long Term: $11,924
Sessional Lecturer III: $11,924
Sessional Lecturer III Long Term: $12,202
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.
Qualifications: Preferably candidates will have a completed, or nearly completed, PhD degree in an area related to the course or a Master’s degree plus extensive professional experience in an area related to the course. Teaching experience is preferred.
Brief description of duties: Preparing course materials; delivering course content (e.g., seminars, lectures, and labs); developing and administering course assignments, tests & exams; grading; holding regular office hours.
Application Deadline: May. 28, 2026
Application Process: Applicants must submit a CV and a completed CUPE 3902 Unit 3 application form in one pdf file to the attention of:
Nafiseh Yazdian, Administrative Coordinator
Faculty of Information, 140 St. George Street University of Toronto
This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II and Sessional Lecturer III in accordance with Article 14:12.
Diversity Statement
The University of Toronto embraces Diversity and is building a culture 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 demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.
Accessibility Statement
The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.
If you require any accommodations at any point during the application and hiring process, please contact [email protected].
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