Data Science / data analytics, Data Science, Data Science and Information Technology, Machine Learning
(posted 2020/12/10, listed until 2021/02/17)| Position ID: | UofT-iSchool-HCDS [#17766, 1750] |
| Position Title: | Assistant Professor - Human Centered Data Science |
| Position Type: | Tenured/Tenure-track faculty |
| Position Location: | Toronto, Ontario M5S3G6, Canada [map] |
| Subject Areas: | Artificial Intelligence Data Science / data analytics, Data Science, Data Science and Information Technology, Machine Learning |
| Appl Deadline: | 2021/02/17 11:59PM (posted 2020/12/10, listed until 2021/02/17) |
| Position Description: |
Date Posted: 12/09/2020
THIS POSTING HAS BEEN EXTENDED TO THE NEW CLOSING DATE OF FEBRUARY 17, 2021 Description:
The Faculty of Information at the University of Toronto invites applications for a full-time tenure stream position at the rank of Assistant Professor in the area of Human Centered Data Science. The expected start date is July 1, 2021, or shortly thereafter.
Applicants must have a Ph.D. in Information, Computer Science, Statistical Sciences, Electrical and Computer Engineering, or a related area by the time of appointment, or shortly thereafter, with a demonstrated record of excellence in research and teaching. We seek applicants whose research takes a human and/or social approach to data science with a core emphasis in artificial intelligence or machine learning. The successful candidateâs research and teaching interests will complement and build upon our existing strengths (https://ischool.utoronto.ca/research/). Candidate's area of research must focus on one or more of the following areas: explainability, interpretability, and transparency of algorithms; models and predictions; fairness and debiasing of data, algorithms, models, and predictions; preservation and safeguarding of privacy and/or confidentiality. Industrial experience in a related area is considered an asset.
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. 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 Facultyâs rigorous, highly-ranked Master of Information, Bachelor of Information, and PhD programs.
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 standing.
Research excellence will be evaluated commensurate with the career stage of the candidate, taking into consideration the life, trajectory and any special circumstances (e.g., career interruptions) as outlined in the submitted materials. Evidence of excellence in teaching will be provided through the teaching dossier submitted as part of the application and strong endorsements by referees. The teaching dossier must include a statement of teaching philosophy, a summary of teaching experience, interests, and accomplishments, sample course materials (e.g., syllabi), and teaching evaluations or other evidence of superior performance in teaching-related activities. 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.
The successful candidate must also provide evidence of readiness as a research supervisor in the application materials, as they will be expected to undertake undergraduate and graduate research supervision and teaching, and to perform standard professional and administrative activities typical of a research-intensive university-level department.
Equity and diversity are essential to academic excellence. We seek candidates who value diversity and whose research, teaching, and service bear out our commitment to equity.
As part of the University of Toronto, the Faculty of Information offers the opportunity to conduct research, teach, and live in one of the most diverse cities in the world. Because of our campusâ incredibly diverse student body, and our Facultyâs commitment to fostering an environment of diversity and inclusion, we seek candidates who demonstrate a commitment to equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment through their application materials. Candidates therefore must submit a statement of contributions to equity and diversity, which might cover topics such as (but not limited to): research or teaching that incorporates a focus on underrepresented communities, the development of inclusive pedagogies, or the mentoring of students from underrepresented groups.
Salary will be commensurate with qualifications and experience.
The Faculty of Information (iSchool) https://ischool.utoronto.ca/ 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 online by clicking the link below. Applications must include:
Applicants must also arrange to have three letters of reference sent directly by the referee via email (on letterhead, dated, and signed) to dean.ischool@utoronto.ca by the closing date. PLEASE NOTE: this search is not using the Universityâs automatic solicitation and collection functionality for reference letters.
All application materials must be submitted online. Submission guidelines can be found at: http://uoft.me/how-to-apply. If you have questions about this position, please contact dean.ischool@utoronto.ca.
The closing date for applications is February 17, 2021 and all application materials, including reference letters, must be received by then.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
Diversity Statement
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.
Accessibility Statement
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.
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