Assistant Professor, Teaching Stream - Human-Centred Data Sciences

University of Toronto

Application Deadline: 4 September 2025, 11:59PM ET

The Faculty of Information at the University of Toronto invites applications for a full-time teaching stream position in Human-Centred Data Sciences. The appointment will be at the rank of Assistant Professor, Teaching Stream with an anticipated start date of July 1, 2026.

This search aligns with the University’s commitment to strategically and proactively promote diversity among our community members (Statement on Equity, Diversity & Excellence). Recognizing that Black, Indigenous, and other Racialized communities have experienced inequities that have developed historically and are ongoing, we strongly welcome and encourage candidates from those communities to apply. 

Preference will be given to candidates who self-identify as Indigenous. Recognizing that there are a variety of terms that potential candidates may use to self-identify, the University uses the term “Indigenous” in this search, which forms part of the U of T Response to Canada’s Truth and Reconciliation Commission, to encompass the people of Turtle Island, including those who identify as First Nations, Métis, Inuk (Inuit), Alaska Native, Native American, and Native Hawaiian people.

Applicants must have earned a PhD degree by the time of appointment, or shortly thereafter. Alternatively, applicants must have a Master’s degree with at least five (5) years of teaching experience. Relevant fields of study for both PhD and Master's include, but are not limited to: Information, Computer Science, Engineering, Statistical Sciences, Information Systems, Software Engineering, and Computational Social Science. Preference will be given to candidates with a PhD. 

Candidates must have a demonstrated record of excellence in teaching. We seek candidates whose teaching interests complement and enhance our existing departmental strengths. Candidates must have a strong technical background and the capability to teach technical and computational electives, including but not limited to courses such as INF1340H – Programming for Data Science, INF1344H – Introduction to Statistics for Data Science, INF2178H – Experimental Design for Data Science, and INF2190H – Introduction to Data Analytics. Experience teaching technical subjects such as programming, data science, machine learning, and algorithmic fairness is highly desirable.

Candidates must have teaching experience in a degree-granting program, including lecture preparation and delivery, curriculum development, and development of online material/lectures. We prioritize candidates who have been sole instructors in the classroom and who have a teaching/pedagogical-centric CV. Experience as a teaching assistant is valued, but preference will be given to those with primary instructional responsibility. Additionally, candidates must possess a demonstrated commitment to excellent pedagogical inquiry and a demonstrated interest in teaching-related scholarly activities. 

Some priority areas for teaching and scholarship of teaching and learning (SOTL) include:

• Design, creation, and management of cultural databases

• Algorithmic fairness, accountability, transparency, and bias

• Public interest technology

• Data science pedagogy

We especially welcome candidates with experience in data science tools and techniques (e.g., Python, R), database design and management, algorithmic auditing, human-centered design, and interdisciplinary research methods bridging technical, social, and ethical dimensions of data science.

The successful candidate will be expected to teach at both the undergraduate and graduate levels, and in at least two of our four degree programs (Bachelor of Information, Master of Information, Master of Museum Studies, PhD). Experience with innovative teaching methods, curriculum design for inclusivity and accessibility, and a commitment to fostering equity, diversity, and inclusion in both research and teaching are essential.

There is potential for the successful candidate to take up leadership of the Digital Curation Institute (DCI), particularly if their teaching and research align with cultural database management or public interest technology. This is an opportunity, not a requirement, and will be discussed further with the successful candidate.

Evidence of excellence in teaching and a commitment to excellent pedagogical inquiry can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application (with required materials outlined below) as well as strong letters of reference. Pedagogical research, teaching awards, and/or grants related to teaching technical subjects are considered assets.

Salary will be commensurate with qualifications and experience.

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

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