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 and adjacent fields, based at 700 University Avenue, Toronto, ON. The appointment will be at the rank of Assistant Professor, with an anticipated start date of July 1, 2027.
Research focus:
We seek exceptional candidates 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 (earned by the time of appointment or shortly thereafter)
- Demonstrated record of excellence in research and teaching in Data Science Computation or adjacent fields
- Evidence of research excellence: publications in top-ranked journals, research statement, conference presentations, awards, and strong referee endorsements
- Evidence of teaching excellence: teaching accomplishments, teaching dossier, and strong letters of reference
- Commitment to equity, diversity, inclusion, and collegial learning environments
- Experience working with, teaching, or mentoring diverse groups is preferred
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 by the time of appointment or shortly thereafter
- Demonstrated excellence in research and teaching in Data Science Computation or adjacent fields
- Evidence of research excellence through publications, research statements, conference presentations, awards, and strong referee endorsements
- Evidence of teaching excellence through teaching accomplishments, a teaching dossier, and strong letters of reference
- Commitment to equity, diversity, inclusion, and collegial learning environments
- Experience working with, teaching, or mentoring diverse groups
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