Sessional Lecturer: CHL5223H Applied Bayesian Methods

University of Toronto; Toronto; On-site; CAD 4,200 - 8,400; Part time

Job summary

The University of Toronto invites applications for a Sessional Lecturer position CHL5223H Applied Bayesian Methods at the Dalla Lana School of Public Health, St. George campus in Toronto. The course runs Jan 6 to Apr 9, 2027, with TA support of 70 hours and in-person lectures Mondays 2:00–5:00 p.m.

Minimum qualifications include a PhD in Biostatistics, Statistics, or a related field with advanced Bayesian knowledge and demonstrated teaching excellence. Compensation follows CUPE 3902 Unit 3 terms.

Qualifications

• PhD in Biostatistics, Statistics, or related field.
• Advanced understanding of Bayesian methods.
• Experience teaching a similar course.

Responsibilities

• Prepare course content and syllabus.
• Deliver weekly 3-hour lectures and hold scheduled office hours.
• Respond to student questions and provide regular feedback.
• Prepare, grade and invigilate course assessments; manage final grades.

Skills

Bayesian statistics

Teaching experience

Education

PhD in Biostatistics or Statistics

Job description

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Sessional Lecturer: CHL5223H Applied Bayesian Methods

Date Posted: 09/28/2026
Req ID: 50349
Faculty/Division: Dalla Lana School of Public Health
Department: Dalla Lana School of Public Health
Campus:St. George (Downtown Toronto)
Existing Vacancy: Yes

Course Description & Learning Objectives: Bayesian methods are important tools for applied statisticians, biostatisticians, and data scientists. They provide a flexible framework for quantifying uncertainty and learning from new data. The course introduces the basics of Bayesian inference and Markov chain Monte Carlo methods, then shows students how to compute and make inferences for complex data problems. The learning objectives are to gain (i) an understanding of basic Bayesian inference, (ii) an understanding of the basic theory of Markov chain Monte Carlo methods, and (iii) proficiency in performing Bayesian data analysis on complex data problems.

Estimated TA support: 70 hours

Class Schedule: Mondays, 2:00 p.m. to 5:00 p.m. (in person)

Sessional dates: January 6 to April 9, 2027

(Salary inclusive of 4% or 6% vacation pay, where applicable)

Please note that should rates stipulated in the Collective Agreement vary from rates stated in this posting, the rates stated in this posting shall prevail.

Minimum Qualifications: PhD in Biostatistics, Statistics, or a related field. Advanced comprehension of Bayesian methods, as evidenced by research activity and/or advanced teaching experience. Preference will be given to candidates with demonstrated experience of excellence in teaching a similar course.

Description of duties: Prepare course content and syllabus, prepare and give weekly 3-hour lectures; hold scheduled office hours for at least an hour per week; respond to student questions regarding the course and course materials; provide regular feedback to students; prepare, grade and invigilate course assessments; manage and submit the final course grades.

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.

It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.

Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.

Diversity Statement

The University of Toronto embraces Diversity and is building aculture of belonging that increases our capacity to effectivelyaddress and serve the interests of our global community. Westrongly encourage applications from Indigenous Peoples,Black and racialized persons, women, persons withdisabilities, and people of diverse sexual and gender identities.We value applicants who have demonstrated a commitment toequity, diversity and inclusion and recognize that diverseperspectives, experiences, and expertise are essential tostrengthening our academic mission.

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 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 [e-mail] .