University of Toronto, Faculty of Information

Position ID:University of Toronto-Faculty of Information-DATASCIENCE [#16135, 2000407]
Position Title: Associate Professor / Professor - Data Science
Position Type:Tenured/Tenure-track faculty
Position Location:Toronto, Ontario M5S3G6, Canada
Subject Areas: Data Science / Data Science, Computational Social Science, data analytics, Machine Learning
Artificial Intelligence
Data Visualization
Appl Deadline:2020/04/27help popup (posted 2020/03/04, listed until 2020/04/27)
Position Description:    

*** the list date or deadline for this position has passed. ***

The Faculty of Information at the University of Toronto invites applications for a tenure-stream position at the rank of Associate Professor or Professor in Data Science. The expected start date is September 1, 2020, or shortly thereafter. 

We seek applicants whose research takes a human and/or social approach to data science, and whose research and teaching interests will complement and strengthen our existing strengths.

Candidates must demonstrate an exceptional record of excellence in research 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, or Computer Science, or Statistical Sciences or Electrical and Computer Engineering, or a related field. 

Candidates must have an outstanding record of excellence in teaching and research, and an established internationally recognized program of world-class scholarship, combined with experience with working across faculties/departments and disciplines. The successful candidate will be expected to sustain and lead an outstanding, innovative, independent, and externally funded research program of the highest international calibre. 

Excellence in research will be demonstrated by a record of sustained high impact contributions to the field; significant output of research with an internationally recognised impact; sustained contributions and publications in top ranked, internationally recognized, and field relevant academic journals; presentations at significant conferences; distinguished awards and accolades; other noteworthy activities and contributions to the visibility and prominence of the discipline; and strong endorsements by referees of high international stature. 

Evidence for excellence in teaching will be provided through strong letters of reference; teaching accomplishments; awards and accolades; and a teaching dossier submitted as part of the application to include a reflective teaching statement, sample syllabi, and strong teaching evaluations. 

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; three sample publications; and a detailed teaching dossier including a statement of teaching philosophy, sample course materials, and teaching evaluations. 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 April 27, 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.

This employer is not accepting applications for this position through AcademicJobsOnline.Org. Please apply at https://utoronto.taleo.net/careersection/10050/jobdetail.ftl?job=2000407&tz=GMT-05%3A00&tzname=America%2FNew_York.
Contact: Anna Pralat
Email: email
Postal Mail:
140 St. George Street
Toronto, ON M5S 3G6
Canada
Web Page: https://ischool.utoronto.ca/

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