Assistant Professor, Teaching Stream - Contractually Limited Term Appointment - Statistical Sci...
- University of Toronto
- Toronto, ON
- Faculty Jobs
- Engineering & Mathematics, Mathematics, Statistics
- Position Type
- Assistant Professor
- Employment Type
- Full Time
- Institution Type
- Four-Year Institution
Date Posted: 02/27/2023
Closing Date: 04/10/2023, 11:59PM ET
Req ID: 29654
Job Category: Faculty - Teaching Stream, Contractually Limited Term Appointment
Faculty/Division: Faculty of Arts & Science
Department: Department of Statistical Sciences
Campus: St. George (Downtown Toronto)
The Department of Statistical Sciences in the Faculty of Arts and Science at the University of Toronto invites applications for up to three (3) Contractually Limited Term Appointments (CLTA) in Statistical Sciences. The appointments will be at the rank of Assistant Professor, Teaching Stream for a one-year term anticipated to begin on July 1, 2023.
Applicants must have at least a Masters degree in Statistics, Biostatistics, Data Science, or a related discipline by the time of appointment. A PhD in these areas by the time of the appointment, or shortly thereafter is preferred.
Applicants must have a minimum of one-year experience teaching a variety of university level courses in Statistics or Data Science that include computation using R, Python, or another programming language. The successful applicant should be prepared to teach advanced and introductory undergraduate statistics and data science courses to students with a range of mathematical and computational backgrounds. A full list of courses can be found at https://artsci.calendar.utoronto.ca/section/Statistical-Sciences.
Candidates must have a demonstrated record of excellence in statistics or data science teaching, including lecture preparation and delivery of innovative course materials, activities and assessments with a demonstrated commitment to pedagogical growth. Experience teaching large classes is considered an asset. We seek candidates whose teaching interests complement and strengthen our existing departmental strengths in Statistical Sciences.
Evidence of excellence in teaching and a commitment to pedagogical growth can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application including a strong teaching statement, sample syllabi and course materials, and teaching evaluations, as well as strong letters of reference from referees of high standing.
Candidates are also expected to show evidence of a commitment to equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment demonstrated through the application materials.
Salary will be commensurate with qualifications and experience.
All qualified candidates are invited to apply online at Academic Jobs Online, https://academicjobsonline.org/ajo/jobs/24418 and must submit a cover letter; a current curriculum vitae; and a complete teaching dossier to include a teaching statement, sample syllabi and course materials, and teaching evaluations. Equity and diversity are essential to academic excellence. We seek candidates who value diversity and whose teaching and service bear out our commitment to equity. Candidates therefore must submit a 1-2 page statement of contributions to equity and diversity, which might cover topics such as (but not limited to): teaching that incorporates a focus on underrepresented communities, the development of inclusive pedagogies, or the mentoring of students from underrepresented groups.
Applicants must also arrange to have three letters of reference (on letterhead, dated and signed) uploaded through Academic Jobs Online directly by the writers by the closing date. At least one reference letter must primarily address the candidate’s teaching.
All application materials, including signed reference letters, must be received by April 10, 2023.
For more information about the Department of Statistical Sciences, please visit our website at https://www.statistics.utoronto.ca or contact Katrina Mintis at [email protected].
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.
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.
If you require any accommodations at any point during the application and hiring process, please contact [email protected].
Job Segment: Statistics, Equity, Academic, Teacher, Data, Finance, Education
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