Assistant Professor, Teaching Stream - Human-Centred Data Sciences
Date Posted: 07/09/2025
Closing Date: 09/04/2025, 11:59PM ET
Req ID: 43238
Job Category: Faculty - Teaching Stream (continuing)
Faculty/Division: Faculty of Information
Department: Faculty of Information
Campus: St. George (Downtown Toronto)
Description:
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.
The Faculty of Information is a research-led Faculty committed to educating the next generation of professional and academic leaders in information, who join us in transforming society through collaboration, innovation, and knowledge creation. We are guided by core values that include engagement with cultural, social, political, and ethical issues in information to benefit society; and transparency, accountability, and public responsibility. With an outstanding and award-winning faculty, our key strengths are the quality of our interdisciplinary research, the abilities of our graduate students, close ties across the university, and committed alumni. Our strategic priorities are excellence through interdisciplinarity, impact through partnerships, and equity through fostering inclusive environments. We are especially proud of the calibre, excellence, academic engagement, and diversity of our students.
As part of the University of Toronto, the Faculty of Information offers the opportunity to teach, research, and live in one of the most diverse cities in the world. We seek candidates who have demonstrated a commitment to equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment through their application materials. Candidates therefore must submit a statement of contributions to equity and diversity, which might cover topics such as (but not limited to): teaching or research that incorporates a focus on underrepresented communities, the development of inclusive pedagogies, or the mentoring of students from underrepresented groups.
All qualified candidates are invited to apply online by clicking the link below. Applicants must submit
- a cover letter;
- a current curriculum vitae (CV);
- a statement of contributions to equity, diversity, inclusion, and accessibility (as outlined above); and,
- a complete teaching dossier which includes a teaching statement, sample syllabi and course materials, and teaching evaluations.
Applicants must provide the name and contact information of three references. The University of Toronto’s recruiting tool will automatically solicit and collect letters of reference from each referee the day after an application is submitted. Applicants remain responsible for ensuring that references submit recent letters (on letterhead, dated and signed) by the closing date. At least one reference letter must primarily address the candidate’s teaching. More details on the automatic reference letter collection, including timelines, are available in the candidate FAQ.
Submission guidelines can be found at http://uoft.me/how-to-apply. Your CV and cover letter should be uploaded into the dedicated fields. Please combine additional application materials into one or two files in PDF/MS Word format. If you have any questions about this position, please contact Melissa Szopa, Administrative Coordinator, Academic at dean.ischool@utoronto.ca.
All application materials, including recent reference letters, must be received by Thursday, September 4, 2025.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
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 uoft.careers@utoronto.ca.
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Database, Computer Science, Curriculum Development, Information Systems, Software Engineer, Technology, Education, Engineering