Sessional Lecturer, INF- Experimental Design Data Science

University of Toronto
Faculty of Information

Sessional Lecturer

Winter Term 2027 (January 2027 - April 2027)

Course

Description:

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 (INF
2178H — 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

Salary:
Sessional Lecturer I: $10,889
Sessional Lecturer I Long Term: $11,652
Sessional Lecturer II $11,652
Sessional Lecturer II Long Term: $11,924
Sessional Lecturer III: $11,924
Sessional Lecturer III Long Term: $12,202

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 professional 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.

Final date to receive applications: September 8, 2026

Application Process: