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THIS POSTING HAS BEEN EXTENDED TO THE NEW CLOSING DATE OF MAY 11, 2020.
Job Field: Tenure Stream
Faculty / Division: Faculty of Information
Department: Faculty of Information
Campus: St. George (downtown Toronto)
Reference: 2000398
Job Closing: May 11, 2020, 11:59pm EST
The Faculty of Information at the University of Toronto invites applications for a tenure stream position at the rank of Assistant Professor in Data Science. The position start date is July 1, 2020, or shortly thereafter.
We seek applicants whose research takes a human and/or social approach to data science. The successful candidate’s research and teaching interests will complement and build upon our existing strengths. Applicants must have research expertise in artificial intelligence, data analytics, data visualization, intelligent systems, machine learning, business intelligence, or a related area, and be working at the interaction of data science and other disciplines such as the humanities, business, education, law, and healthcare.
Applicants must have a Ph.D. in Information, Computer Science, Statistical Sciences, Electrical and Computer Engineering, or a related field by the time of appointment or shortly thereafter.
The successful candidate must have a proven record of research excellence, experience with working across faculties/departments and disciplines, demonstrated excellence in teaching and the demonstrated ability and ambition to advance our Faculty’s rigorous, highly-ranked Master of Information and PhD programs. The successful candidate will be expected to conduct innovative and independent research at the highest international level and to establish an outstanding, competitive, and externally funded research program.
Evidence of excellence in research will be demonstrated primarily by publications or forthcoming publications in leading journals or conferences in the field, the submitted research statement, presentations at significant conferences, awards and accolades, and strong endorsements by referees of high international standing. Industrial experience in a related area is considered an asset.
Evidence of excellence in teaching will be provided through the teaching dossier submitted as part of the application to include a teaching philosophy statement, a summary of teaching experience, interests, and accomplishments, sample course materials, and teaching evaluations or other evidence of superior performance in teaching-related activities, as well as strong endorsements by referees. Other teaching-related activities can include performance as a teaching assistant or course instructor, experience leading successful workshops or seminars, student mentorship, or excellent conference presentations or posters.
Salary will be commensurate with qualifications and experience.
The Faculty of Information (iSchool) at the University of Toronto is a research-led Faculty, committed to educating the next generation of professional and academic leaders in Information, who join us in transforming society through collaboration, innovation, and knowledge creation. We are guided by core values that include engagement with cultural, social, political, and ethical issues in information to benefit society and transparency, accountability, and public responsibility. With an outstanding complement of 30 award winning faculty members, our key strengths are the quality of our research, the abilities of our graduate students, close ties across the university, and committed alumni. The Faculty of Information is especially proud of the calibre, excellence, academic engagement, and diversity of the students it recruits, admits, and graduates.
All qualified candidates are invited to apply by clicking the link below. Applications must include a cover letter; curriculum vitae; a research statement outlining current and future research interests and a list of recent or forthcoming publications; up to three samples of recent scholarly work (e.g., an article or book chapter); and a detailed teaching dossier including a statement of teaching philosophy, a summary of teaching experience, interests, and accomplishments, sample course materials, and teaching evaluations or evidence of superior performance in other teaching-related activities as listed above.
Applicants must also arrange to have three letters of reference sent directly by the referee via email (on letterhead and signed) to anna.pralat@utoronto.ca by the closing date. If you have questions about this position, please contact anna.pralat@utoronto.ca.
All application materials must be submitted online. Submission guidelines can be found at: http://uoft.me/how-to-apply. We recommend combining attached documents into one or two files in PDF/MS Word format.
The closing date for applications is May 11, 2020, and all application materials, including reference letters, must be received by then.
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.
As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
Click here to apply: https://utoronto.taleo.net/careersection/10050/jobdetail.ftl?job=509801
