[Air-L] Human-Centred Data Sciences - Assistant Professor, Teaching Stream

[Evan Light]

Hey folks - be on the lookout for more postings this summer. You can 
keep an eye out here, too. https://ischool.utoronto.ca/about-us/jobs/


*Human-Centred Data Sciences - Assistant Professor, Teaching Stream*

*Faculty of Information, University of Toronto*

*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 
<https://governingcouncil.utoronto.ca/secretariat/policies/equity-diversity-and-excellence-statement-december-14-2006>). 
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 <https://ischool.utoronto.ca/>. 
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 <https://ischool.utoronto.ca/> 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 <https://www.utoronto.ca/>, 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 
<https://jobs.utoronto.ca/content/Frequently-Asked-Questions/?locale=en_US>. 


Submission guidelines can be found at http://uoft.me/how-to-apply 
<https://jobs.utoronto.ca/content/Frequently-Asked-Questions/>. 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 at 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 at utoronto.ca.

Apply Here: 
<https://jobs.utoronto.ca/job/Toronto-Assistant-Professor,-Teaching-Stream-Human-Centred-Data-Sciences-ON/593875717/>

-- 
Evan Light
Associate Professor, Policy Studies
Coordinator, Critical Information Policy Studies
Faculty of Information / iSchool
University of Toronto
https://ischool.utoronto.ca