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 Data Science Computation or adjacent fields, based at 700 University Avenue, Toronto, ON. The appointment will be at the rank of Associate Professor or Professor, with an anticipated start date of July 1, 2027.
Research focus:
We seek exceptional candidates with an established international reputation whose research advances the theoretical and methodological foundations of computation in data science, including 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.
Qualifications:
- PhD in Statistics, Computer Science, Data Science, or a closely related discipline
- Clearly demonstrated record of excellence in research and teaching, with sustained high-impact contributions and publications in top-ranked journals
- Research statement, presentations at significant conferences, distinguished awards, and strong endorsements from referees of high standing
- Evidence of teaching excellence: teaching accomplishments, teaching dossier, and strong letters of reference
- Commitment to equity, diversity, inclusion, and collegial learning environments
- Research and teaching interests that complement the department's existing strengths
The University of Toronto is committed to equity, diversity, and excellence, and strongly welcomes and encourages applications from Black, Indigenous, and other Racialized communities.
To apply, click Apply to submit your application through the original job posting.
Skills Required
- PhD in Statistics, Computer Science, Data Science, or a closely related discipline
- Established international reputation and sustained high-impact research contributions
- Publications in top-ranked journals
- Clearly demonstrated record of excellence in research and teaching
- Research statement and evidence of significant conference presentations or distinguished awards
- Strong endorsements and letters of reference from highly regarded referees
- Evidence of teaching excellence, including teaching accomplishments and a teaching dossier
- Commitment to equity, diversity, inclusion, and collegial learning environments
- Research and teaching interests that complement the department’s existing strengths
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