Assistant Professor – Statistical Learning Theory

Statistics Interest Group; Toronto; On-site; CAD 140,000 - 190,000; Full time

Job summary

University of Toronto invites applications for a full-time tenure-stream Assistant Professor in Statistical Learning Theory and related fields, with an anticipated start date of July 1, 2027. The search emphasizes equity, diversity and excellence in research and teaching.

Responsibilities include establishing a nationally and internationally recognized research program and contributing to teaching and service within the Department of Statistical Sciences. Applications are due by November 9, 2026.

Qualifications

• PhD in Statistics, Computer Science, Data Science, or closely related discipline.
• Record of research and teaching excellence in Statistical Learning Theory.
• Experience mentoring diverse groups of students is preferred.

Responsibilities

• Establish innovative, independent research at an international level and build a competitive, externally funded program.
• Teach and service with a teaching and service load appropriate for the position.
• Maintain a commitment to equity, diversity, inclusion and a respectful learning and working environment.

Skills

Statistical learning theory

Research excellence

Teaching excellence

Education

PhD in Statistics/CS/Data Science

Job description

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.

EEO STATEMENT

Equity, diversity, and inclusion are essential to academic excellence as articulated in University of Toronto’s Statement on Equity, Diversity and Excellence.

REQUIREMENTS AND QUALIFICATIONS

• PhD in Statistics, Computer Science, Data Science, or a closely related discipline, earned by the time of appointment or shortly thereafter.
• Demonstrated record of excellence in research and teaching in Statistical Learning Theory.
• Experience working with, teaching, or mentoring diverse groups or students is preferred.
• Research record: publications in top‑ranked and field‑relevant journals or forthcoming papers meeting high international standards, research statement, presentations, awards, and strong referee endorsements.
• Teaching excellence demonstrated by teaching accomplishments, teaching dossier, and strong letters of reference.

RESPONSIBILITIES

• Establish innovative, independent research at an international level and build an outstanding, competitive, externally funded research program.
• Teach and serve with a teaching and service load appropriate for the position.
• Maintain a commitment to equity, diversity, inclusion and a respectful, collegial learning and working environment.

HIRING SALARY RANGE

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

APPLICATION PROCESS

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

Qualified candidates should apply online. Materials to submit include:

• Cover letter
• Curriculum vitae
• Complete teaching dossier: teaching statement, sample syllabi and course materials, teaching evaluations
• Three letters of reference, signed and dated, submitted by the writers via the application system

Contact: Katrina Mintis, [e-mail]

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 is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). We strive to make recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

NOTE

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