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Added 21 mins ago
Student Warehouse Associate
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Full-time
…Accessibility for Ontarians with Disabilities Act (AODA). Our Human Resources team is responsible for working with applicants requesting an accommodation at any stage of the hiring…
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Sales Associate - Full-time / Part-time
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University of Toronto

Associate Professor/Professor - Data Science Computation

Toronto, ON, Canada

Pay: $200,000 CAD / year
Apply by: Dec 8, 2026
Posting language: English
Posted: Sep 24, 2026

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Original job description

Date Posted: 09/24/2026
Closing Date: 12/07/2026, 11:59PM ET
Req ID: 50282
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 Data Science Computation or adjacent fields. The appointment will be at the rank of Associate Professor or 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

Applicants must have earned a PhD degree in Statistics, Computer Science, Data Science, or a closely related discipline by the time of appointment, with a clearly demonstrated record of excellence in research and teaching in Data Science Computation or adjacent fields. We are seeking exceptional candidates whose research advances the theoretical and methodological foundations of computation in data science, including, but not limited to, sampling and simulation, computational inference, optimization, randomized numerical methods, and scalable algorithms for high-dimensional problems, with particular interest in statistical-computational tradeoffs, complexity, convergence, and theoretical guarantees. Candidates must have an established international reputation.

We seek candidates whose research and teaching interests complement and strengthen our existing departmental research areas https://www.statistics.utoronto.ca/research.

Candidates must provide evidence of research excellence, as demonstrated by a record of sustained high-impact contributions and publications in top-ranked and field relevant journals, the submitted research statement, presentations at significant conferences, distinguished awards and accolades, and other noteworthy activities that contribute to the visibility and prominence of the discipline, as well as strong endorsements from referees of high standing.

Evidence of excellence in teaching will be demonstrated through teaching accomplishments, the teaching dossier (including the required materials outlined below), and strong letters of reference.

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.

RESPONSIBILITIES

Candidates will be expected to sustain and lead innovative and independent research at the highest international level and to maintain an outstanding, competitive, and externally funded program.

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

HIRING SALARY RANGE

The rank and salary will be commensurate with qualifications and experience. The salary range for this position exceeds $200,000 CAD per annum.

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 recent signed reference letters, must be received by December 7, 2026.

All qualified candidates are invited to apply online at Academic Jobs Online, https://academicjobsonline.org/ajo/jobs/32804. Applicants must submit the following materials:

a cover letter;
a current curriculum vitae;
a research statement outlining current and future research interests;
one recent publication;
a complete teaching dossier, including
- a teaching statement,
- sample syllabi and course materials, and

- teaching evaluations
Applicants must also arrange to have three recent 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.

The University of Toronto has adopted the AAU Principles on Preventing Sexual Harassment in Academia, including the requirement that applicants release personnel information from prior employers regarding sexual misconduct. Full details and requirements can be found here.

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.

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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More about this job

Responsibilities

The successful candidate will lead innovative and independent research at the highest international level while maintaining an externally funded program. They will also be responsible for teaching courses and performing service duties within the department.

Requirements

Applicants must hold a PhD in Statistics, Computer Science, Data Science, or a closely related discipline. Candidates are expected to have an established international reputation and a demonstrated record of excellence in research and teaching.

Skills

Data Science
Computation
Statistics
Computer Science
Sampling
Simulation
Computational Inference
Optimization
Randomized Numerical Methods
Scalable Algorithms
High-dimensional Problems
Statistical-computational Tradeoffs
Complexity
Convergence
Theoretical Guarantees

Visa sponsorship

Not detected in the job text

Hiring contact

Katrina Mintis

Hiring contact email

katrina.mintis@utoronto.ca

Keywords

Data Science
Computation
Statistics
Computer Science
Sampling
Simulation
Computational Inference
Optimization
Randomized Numerical Methods
Scalable Algorithms
High-dimensional Problems
Statistical-computational Tradeoffs
Complexity
Convergence
Theoretical Guarantees
Tenure Stream
Faculty
Research
Teaching
Academic
Higher Education

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