University of Toronto, Statistical Sciences

Position ID:UofT-Statistical Sciences-CLTAS [#27350]
Position Title: Assistant Professor, Teachingh Stream, Contractually Limited Term Appointment
Position Type:Non tenure-track faculty
Position Location:Toronto, Ontario M5G 1X6, Canada [map] sort by distance
Subject Areas: Statistics / Statistics
Data Science
Appl Deadline:2024/04/24 11:59PMhelp popup* (posted 2024/03/14, listed until 2024/09/14)
Position Description:    

*** the listing date or deadline for this position has passed and new applications are no longer accepted. ***

The Department of Statistical Sciences in the Faculty of Arts and Science at the University of Toronto invites applications for up to three (3) contractually-limited term appointments (CLTA) in the field of Statistical Sciences. Each appointment will be at the rank of Assistant Professor, Teaching Stream for a one-year term with an anticipated start date of July 1, 2024.


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 applicants from those communities to apply.


Applicants are required to have earned a Ph.D. in Statistics, Biostatistics, Data Science or a related field by the time of appointment or shortly thereafter. Alternatively, applicants are required to have (i) a Masters in Statistics, Biostatistics, Data Science or related field with (ii) at least 18 months of excellent teaching experience in a degree-granting program/post-secondary institution, and (iii) demonstrated excellent scholarly or creative professional activity in areas such as, but not limited to, exemplary teaching practices, development of pedagogical software tools, course or curriculum development, or engagement with Statistics, Biostatistics and/or Data Science Education research.


Applicants must have a minimum of one-year experience teaching a variety of university level, degree granting courses in Statistics, Biostatistics or Data Science that include computation using R, Python, or another programming language, including lecture preparation and delivery, curriculum development, and development of online material/lectures.  The successful applicant should be prepared to teach advanced and introductory undergraduate statistics and data science courses to students with a range of mathematical and computational backgrounds.  A full list of courses can be found at


Applicants must have a demonstrated record of excellence in teaching statistics, biostatistics or data science teaching, including lecture preparation and delivery of innovative course materials, activities and assessments with a demonstrated commitment to pedagogical growth. Experience teaching large classes is considered an asset. Additionally, applicants must possess a demonstrated commitment to excellent pedagogical inquiry and a demonstrated interest in teaching-related scholarly activities. We seek applicants whose teaching interests complement and strengthen our existing departmental strengths in Statistical Sciences.


Evidence of excellence in teaching and a commitment to pedagogical inquiry can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application including a strong teaching statement, sample syllabi and course materials, and teaching evaluations, as well as strong letters of reference from referees of high standing.


Applicants 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.


Salary will be commensurate with qualifications and experience.


All qualified applicants are invited to apply online at Academic Jobs Online and must submit a cover letter; a current curriculum vitae; and a complete teaching dossier to include a teaching statement, sample syllabi and course materials, and teaching evaluations. Equity and diversity are essential to academic excellence. We seek applicants who value diversity and whose teaching and service bear out our commitment to equity. Applicants therefore must submit a 12 page statement of contributions to equity and diversity, which might cover topics such as (but not limited to):  teaching that incorporates a focus on underrepresented communities, the development of inclusive pedagogies, or the mentoring of students from underrepresented groups.


Applicants must also arrange to have three letters of reference (on letterhead, dated and signed) uploaded through Academic Jobs Online directly by the writers by the closing date. At least one reference letter must primarily address the candidate’s teaching.


All application materials, including signed recent reference letters, must be received by April 25, 2024.


For more information about the Department of Statistical Sciences, please visit our website at or contact Katrina Mintis at


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


Diversity Statement

The University of Toronto is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas.


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.

Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
700 University Avenue
Suite 9005
Toronto, ON M5G 1X6