Assistant Professor - Statistical Learning Theory

Assistant Professor - Statistical Learning Theory

Date Posted: 07/13/2026
Closing Date: 11/09/2026, 11:59PM ET
Req ID: 48743
Job Category: Faculty - Tenure Stream (continuing)
Faculty/Division: Faculty of Arts & Science
Department: Department of Statistical Sciences
Campus: St. George (Downtown Toronto)
Existing Vacancy: Yes

POSITION DESCRIPTION:

The Department of Statistical Sciences in the Faculty of Arts and Science at the University of Toronto invites applications for a full-time tenure stream position in the area of Statistical Learning Theory and adjacent fields. The appointment will be at the rank of Assistant Professor with an anticipated start date of July 1, 2027.

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.

REQUIREMENTS AND QUALIFICATIONS:

Candidates must have earned a PhD degree in Statistics, Computer Science, Data Science, or a closely related discipline by the time of appointment, or shortly thereafter, with a demonstrated record of excellence in research and teaching in the area of Statistical Learning Theory.

The successful candidate should have experience working with, teaching, or mentoring diverse groups or diverse students is preferred. We seek exceptional candidates whose research and teaching interests complement and strengthen our existing departmental research strengths.

Candidates must provide evidence of research excellence which can be demonstrated through 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 high standing.

Evidence of excellence in teaching will be provided through teaching accomplishments, the teaching dossier (the required materials outlined below), as well as strong letters of reference.

RESPONSIBILITIES:

The successful candidate will be expected to establish innovative and independent research at the highest international level and to establish an outstanding, competitive, and externally funded research program.

In addition, the successful candidate will be assigned a teaching and service load.

Candidates are also expected to show evidence of a commitment to equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment demonstrated through the application materials.

HIRING SALARY RANGE:

The expected salary range is $140,000 to $190,000 CAD per annum, depending on experience. Negotiations beyond this salary range will be considered for exceptionally qualified candidates.

ABOUT US:

For more information about the Department of Statistical Sciences, please visit our website at https://www.statistics.utoronto.ca.

For more information on working at the University of Toronto, please visit https://www.utoronto.ca/research-innovation/working-at-uoft.

APPLICATION PROCESS:

All applicant materials, including signed reference letters, must be received by November 9, 2026.

All qualified candidates are invited to apply online at Academic Jobs Online, https://academicjobsonline.org/ajo/jobs/32307Applicants must submit the following materials:

a cover letter; a current curriculum vitae;a complete teaching dossier, includinga teaching statement,sample syllabi and course materials, andteaching evaluationsApplicants must also arrange to have three letters of reference (dated, on letterhead and signed) uploaded through Academic Jobs Online directly by the writers by the closing date.

Equity, diversity, and inclusion are essential to academic excellence as articulated in University of Toronto's Statement on Equity, Diversity and Excellence. We seek candidates who share these values and who demonstrate throughout the application materials their commitment and efforts to advance equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment.

If you have any questions about this position, please contact Katrina Mintis at katrina.mintis@utoronto.ca.

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 uoft.careers@utoronto.ca.

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