Assistant Professor, Teaching Stream - Statistics

Assistant Professor, Teaching Stream - Statistics

Date Posted : 09 / 24 / 2024

Closing Date : 11 / 25 / 2024, 11 : 59PM ET

Req ID : 39712

Job Category : Faculty - Teaching Stream (continuing)

Faculty / Division : Faculty of Arts & Science

Department : Department of Statistical Sciences

Campus : St. George (Downtown Toronto)

Description :

The Department of Statistical Sciences in the Faculty of Arts and Science at the University of Toronto invites applications for a full-time teaching stream position in the area of Statistical Sciences.

The appointment will be at the rank of Assistant Professor, Teaching Stream with an anticipated start date of July 1, 2025.

This search aligns with the University’s commitment to strategically and proactively promote diversity among our community members ( Statement on Equity, Diversity & Excellence ).

Recognizing that Black, Indigenous, and other Racialized communities have experienced inequities that have developed historically and are ongoing, we strongly welcome and encourage candidates from those communities to apply.

Applicants must have earned a PhD in Statistics, Computer Science, Data Science or a related area by the time of appointment, or shortly thereafter with a demonstrated record of excellence in teaching.

We seek candidates whose teaching interests complement and strengthen our existing departmental strengths .

Candidates must have teaching experience in statistics, biostatistics or data science in a degree granting-program at the undergraduate level for Statistics majors and those with a significant mathematical and computational component.

This includes but is not limited to, lecture preparation and delivery, curriculum development, and development of online material / lectures.

Additionally, candidates must possess a demonstrated commitment to excellence in pedagogical inquiry and a demonstrated commitment to excellent pedagogical inquiry and a demonstrated interest in teaching-related scholarly activities.

Candidates must have experience in course preparation including lectures, syllabus, assessments, activities, and delivery of innovative course materials using data from genuine applications of statistical methods.

Candidates must also have experience in collaborating as a statistician or data scientist within a multidisciplinary team on projects involving genuine applications of statistical methodologies and a commitment to excellent pedagogical practices.

Candidates with an interest in supervising undergraduate research projects, experience teaching large classes and managing teaching assistants and experience collaborating with other instructors and teaching assistants on teaching are preferred.

Evidence of excellence in teaching and a commitment to excellent pedagogical inquiry can be demonstrated through teaching accomplishments, awards and accolades, presentations at significant conferences, the teaching dossier submitted as part of the application with required materials outlined below, as well as strong letters of reference from referees of high standing.

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 / 28547 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, diversity and inclusion are essential to academic excellence as articulated in University of Toronto's Statement on Equity, Diversity and Excellence .

We seek candidates who share these values and who demonstrate throughout the application materials their commitment and efforts to advance equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment.

Applicants must also arrange to have three letters of reference ( dated, on letterhead 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 applicant materials, including signed reference letters, must be received by November 25, 2024.

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] .

CAUTION : This ad is posted only to the U of T faculty job board. Please see the information above for application instructions.

Applications submitted via the U of T platform will NOT be considered for this position.

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Diversity Statement

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.

Accessibility Statement

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] .

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