University of Toronto, Department of Statistical Sciences
Location: Toronto, Ontario, Canada
Type: Full Time
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. The appointment will be at the rank of Assistant Professor with an anticipated start date of July 1, 2023.
Applicants must have earned a PhD degree in Statistics or a related area by the time of appointment, or shortly thereafter, with a demonstrated record of excellence in research and teaching. A successful candidate’s research must be in the area of statistical learning which studies, within a statistical framework, methods that use data to make predictions, decisions and inferences.
The successful candidate will be expected to pursue innovative and independent research at the highest international level and to establish an outstanding, competitive, and externally funded research program. Experience working with, teaching, or mentoring diverse groups or diverse students is an asset.
Candidates must provide evidence of research excellence, which can be demonstrated by a record of publications in top-ranked and field-related 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 including a strong teaching statement, sample course materials, and teaching evaluations, as well as 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.
Salary will be commensurate with qualifications and experience.
All qualified candidates are invited to apply online at Academic Jobs Online, https://academicjobsonline.org/ajo/jobs/22672 and must submit a cover letter; a current curriculum vitae; a research statement outlining current and future research interests; a recent writing sample (of no more than 15 pages); and a teaching dossier to include a teaching statement, sample course materials, and teaching evaluations. Equity and diversity are essential to academic excellence. We seek candidates who value diversity and whose research, teaching and service bear out our commitment to equity. Candidates therefore must submit a 1?2 page statement of contributions to equity and diversity, which might cover topics such as (but not limited to): research or 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 (on letterhead, dated and signed) uploaded through Academic Jobs Online directly by the writers by the closing date.
All application materials, including signed reference letters, must be received by November 15, 2022.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
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.
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.