Sessional Lecturer,H - Experimental Design for Data Science (Ontario)

Sessional Lecturer,H - Experimental Design for Data Science (Ontario)

29 Aug
|
University of Toronto
|
Ontario

29 Aug

University of Toronto

Ontario

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Sessional Lecturer, INF2178H - Experimental Design for Data Science
University of Toronto
Faculty of Information

Sessional Lecturer

Winter Term 2027 (January 2027 - April 2027)

At the heart of every Data Science project exists the planning, design and execution of experiments. Such experiments aim at understanding the data, potentially cleaning it and performing the necessary data analysis for knowledge discovery and decision-making. Without knowing the experimental design processes that are used in practice, researchers may not be able to discover what is really hidden in their data. The first aim of this course (INF2178H — Experimental Design for Data Science) is to look at existing experimental designs that take into account the questions that need to be answered as well as the nature of the data and the different parameters used by algorithms.

Subsequently, the course will introduce different qualitative and quantitative methods to assess the quality of the results.

All concepts will be accompanied by examples and the students will have practical exercises and a project in which they will demonstrate their knowledge.

Estimate of the course enrolment: 140

Estimate of TA Support: Estimate of 75 hours with enrollment of 36 or greater. Allocation of TA hours, if any, will be based on enrolment numbers.

Class Schedule: Monday- 2pm to 5pm , Winter-2027 semester.

Sessional dates of appointment: January 1, 2027 - April 30, 2027





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

Qualifications: Preferably candidates will have a completed, or nearly completed, PhD degree in an area related to the course or a Master’s degree plus extensive skilled experience in an area related to the course. Teaching experience is preferred.

Brief description of duties: Preparing course materials; delivering course content (e.g., seminars, lectures, and labs); developing and administering course assignments, tests & exams; grading; holding regular office hours.

Nafiseh Yazdian, Administrative Coordinator
Faculty of Information, 140 St. George Street University of Toronto
[email protected]
This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II and Sessional Lecturer III in accordance with Article 14:12.

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 seehttp://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 [email protected] .

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📌 Sessional Lecturer,H - Experimental Design for Data Science (Ontario)
🏢 University of Toronto
📍 Ontario

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