Associate Professor, Statistical Information

The Faculty of Information and the Department of Statistical Sciences in the Faculty of Arts & Science at the University of Toronto invites applications for a joint (51% Statistical Sciences, 49% Faculty of Information) full time tenure-stream position in the area of Statistical Information. The appointment will be at the rank of Associate Professor with an expected start date of July 1, 2020 or shortly thereafter.

We are interested in candidates that demonstrate an exceptional record of excellence in teaching and research, whose research program includes working across disciplines and complements our existing strengths in both Statistical Sciences and the Faculty of Information. We are particularly interested in research that focuses on replicability issues in science, information-based methods in data science, data privacy, topic models and network analysis.

Applicants must have earned a PhD in Statistical Science or a closely related field. Excellence in research is evidenced primarily by a mature research program with a sustained record of research contributions at the highest international levels expected of a leading researcher, as judged by sustained high impact publications in top ranked and field-relevant academic journals, the submitted research statement, invited presentations at top international conferences, distinguished research awards and accolades, and other noteworthy activities that contribute to the visibility and prominence of the discipline as well as exceptional endorsements by referees of the highest international stature. Evidence for excellence in teaching is based on strong letters of reference, and a teaching dossier containing a strong statement of teaching philosophy, sample syllabi and course materials, teaching accomplishments and accolades and teaching evaluations.

Both units are leaders in transforming society through collaboration, innovation, and knowledge creation. The successful candidate will have an established international reputation and will be expected to sustain and lead innovative and independent research at the highest international level and to maintain an outstanding, competitive externally funded research program; to have a strong commitment to undergraduate and graduate teaching, and to contribute to the enrichment of all aspects of the Department of Statistical Sciences and the Faculty of Information.

The successful candidate will join a vibrant intellectual community of world-class scholars at Canada’s leading university. The Greater Toronto Area offers amazing cultural and demographic diversity and one of the highest standards of living in the world.

Salary is competitive with our North American peers and will be commensurate with qualifications and experience.

Applicants must apply online through AcademicJobsOnline, and include a curriculum vitae, a cover letter, a list of publications, up to three sample publications, a research statement, and a teaching dossier, including a teaching statement, sample syllabi and course materials and teaching

evaluations. Applicants must also arrange to have at least three letters of reference (on letterhead and signed) uploaded through AcademicJobsOnline directly by the writers.

All applicant materials, including signed reference letters, must be received by November 25,2019.

For more information about the Department of Statistical Sciences and the Faculty ofInformation, please visit our websites at and If you have questions about the position please contact Katrina Mintis at This email address is being protected from spambots. You need JavaScript enabled to view it..

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, LGBTQ persons, and others who may contribute to the further diversification of ideas.

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



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