Assistant Professor - Statistical Sciences

University of Toronto; Toronto; On-site; CAD 150,000 - 190,000; Full time

Job summary

A leading Canadian university in Toronto seeks an Assistant Professor in Statistical Sciences for a full-time tenure stream position. The role involves teaching undergraduate statistics courses and conducting research aligned with equity in urban sustainability. Candidates should have a PhD in Statistics or related fields, exemplify excellence in research and teaching, and demonstrate a strong commitment to equity, diversity, and inclusion. The stated salary range is CAD 150,000–190,000 per annum.

Benefits

Competitive salary

Research opportunities

Commitment to diversity and inclusion

Qualifications

• PhD degree in Statistics, Computer Science, Data Science, or related area.
• Demonstrated record of excellence in research and teaching.
• Established strengths in spatial statistics and/or applied machine learning.

Responsibilities

• Develop and teach undergraduate courses in statistics.
• Conduct independent and innovative research.
• Establish and maintain a competitive and externally funded research program.

Skills

Statistical analysis

Research excellence

Teaching ability

Commitment to equity and inclusion

Education

PhD in Statistics or related area

Job description

Assistant Professor - Statistical Sciences

Date Posted: 12/17/2025. Closing Date: 02/17/2026, 11:59PM ET. Req ID: 46152. Job Category: Faculty - Tenure Stream (continuing). Faculty/Division: University of Toronto Scarborough. Department: Department of Computer and Mathematical Sciences. Campus: University of Toronto Scarborough (UTSC).

Description: The Department of Computer and Mathematical Sciences and the Canada Excellence Research Chair Network for Equity in Sustainability Transitions (CERC NEST) at the University of Toronto Scarborough (UTSC) invites applications for a full‑time tenure stream position in the area of Statistical Sciences. The appointment will be at the rank of Assistant Professor, with an anticipated start date of July 1, 2026. The CERC NEST employs a transdisciplinary and comparative approach, working with communities and city actors in Toronto and internationally, to examine how urban sustainability transitions can foster inclusive decision‑making, address regulatory and investment inequities, and ensure a fair distribution of benefits and protection from harms.

Qualifications: Applicants must have earned a PhD degree in Statistics, or a related area (such as Computer Science, Data Science, Quantitative Social Science, Sociology, Economics, Epidemiology, etc.) by the time of appointment or shortly thereafter, with a demonstrated record of excellence in research and teaching. Candidates in all areas of applied statistics will be considered, although candidates are expected to have established strengths in spatial statistics and/or applied machine learning. Grounded in the CERC‑NEST goal of connecting statistics with knowledge co‑production, this hire will have an existing or emerging substantive research agenda related to socio‑environmental challenges of equity in urban sustainability transitions, consistent with the vision, objectives and outcomes of the CERC NEST (https://cercnest.ca/about-us/ ).

Teaching: The successful candidate will have a demonstrated capacity to contribute to an undergraduate curriculum in statistics, which may be demonstrated through teaching accomplishments and experience, and endorsement from referees. We seek exceptional candidates whose research and teaching interests complement and strengthen our existing departmental strengths and dovetail with the CERC NEST strengths. The successful candidate will be expected to mount independent and innovative research, and to establish an outstanding, competitive, and externally funded research program.

Research Excellence: Candidates must provide evidence of excellence in research, which can be demonstrated by a record of publications in top‑ranked and field‑relevant journals or forthcoming publications meeting high international standards, the submitted research statement, presentations at significant conferences, awards and accolades, and strong endorsements from referees of top international stature.

Teaching Excellence: Evidence of excellence in teaching will be demonstrated by teaching accomplishments, and the teaching dossier, including a teaching statement, sample course materials, and teaching evaluations or other evidence of superior performance in teaching‑related activities submitted as part of the application, as well as strong letters of reference. Other teaching‑related activities can include performance as a teaching assistant or course instructor, experience leading successful workshops or seminars, student mentorship, or excellent conference presentations or posters.

Commitment to Equity, Diversity, and Inclusion: Candidates must also show evidence of a commitment to equity, diversity, and inclusion and to the promotion of a respectful and collegial learning and working environment, as demonstrated through the application materials.

Salary: The expected salary range is $150,000–190,000 CAD per annum, depending on experience. Negotiations beyond this salary range will be considered for exceptionally qualified candidates.

UTSC is one of three campuses of the University of Toronto, an institution consistently ranked among the world’s leading research universities and an international leader in statistical research and education. As part of this vibrant academic community, the successful candidate will have the opportunity to teach, conduct research, and live in one of the most diverse metropolitan areas in the world. The appointee will also be a member of the tri‑campus Graduate Department of Statistical Sciences, participating actively in its graduate teaching and supervision.

All qualified candidates are invited to apply online at Academic Jobs Online, https://academicjobsonline.org/ajo/jobs/31426. Applicants must submit a cover letter; a current curriculum vitae; a research statement outlining how current and future research interests fit with the CERC NEST; a recent writing sample (no more than 15 pages in length); and a teaching dossier including a teaching statement, sample course materials, and teaching evaluations or evidence of superior performance in other teaching‑related activities as listed above.

Applicants must also arrange to have three recent letters of reference uploaded through Academic Jobs Online directly by the referees. Applicants remain responsible for ensuring that references submit recent letters (on letterhead, dated, and signed) by the closing date.

All application materials, including recent signed reference letters, must be received by February 17, 2026.

Caution: This ad is “posted only” to the U of T faculty job board. Please see the information above for application instructions. Applications submitted via the U of T platform will NOT be considered for this position.

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.

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 [e-mail].