University of Toronto, Statistical Sciences

Position ID:UofT-Statistical Sciences-CLTA [#21096]
Position Title: Statistical Sciences Assistant Professor, Teaching Stream – Contractually Limited Term Appointment
Position Type:Non tenure-track faculty
Position Location:Toronto, Ontario M5G 1X6, Canada [map]
Subject Area: Statistics
Appl Deadline:2022/03/31 11:59PMhelp popup* (posted 2022/02/02, listed until 2022/08/02)
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 a contractually-limited term appointment (CLTA) in Statistical Sciences. The appointment will be at the rank of Assistant Professor, Teaching Stream for a one-year term anticipated to begin on July 1, 2022.

 

Applicants must have at least a Masters degree in Statistics, Biostatistics, Data Science, or a related discipline by the time of appointment. A PhD in these areas by the time of the appointment, or shortly thereafter is preferred. Applicants must also have a minimum of one-year experience in teaching a variety of university level courses in statistics and be prepared to teach advanced undergraduate statistics courses such as Statistical Consultation, Communication, and Collaboration and Statistical Methods for Machine Learning II, as well as introductory statistics courses for statistics program students.

 

Candidates must have a demonstrated record of excellence in statistics teaching, including lecture preparation and delivery of innovative course materials, activities and assessments; and demonstrate a commitment to pedagogical growth including participation and presentations at education conferences and workshops, publications, and pedagogical choices aligned with scholarship of teaching and learning literature and other scholarly work. Experience teaching large classes are considered assets. We seek candidates whose teaching interests complement and strengthen our existing departmental strengths in both Statistical Sciences.

 

Evidence of excellence in teaching and a commitment to pedagogical growth 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.

 

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. 

 

Salary will be commensurate with qualifications and experience.

 

All qualified candidates 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 candidates who value diversity and whose teaching and service bear out our commitment to equity. Candidates 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 reference letters, must be received by March 31, 2022.

 

For more information about the Department of Statistical Sciences, please visit our website at https://www.statistics.utoronto.ca or contact Katrina Mintis at katrina.mintis@utoronto.ca.

 

All qualified candidates 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:
www.statistics.utoronto.ca
 
700 University Avenue
Suite 9005
Toronto, ON M5G 1X6