SL345090-Fall 2025-UNIV*6080 Computational Thinking for Artificial Intelligence

Sessional Lecturer Work Assignment
Sessional Lecturer, Unit 2
Academic Unit: 
School of Engineering
Semester(s) of Assignment(s): 
Fall 2025
Number of Available Work Assignment(s) / Sections: 
1
Level of Work Assignment(s): 
1
Right of First Refusal (RoFR)
A Sessional Lecturer holds a RoFR (i.e., for a particular course) if they have successfully taught the course in the past six (6) semesters. A SL who holds a RoFR to this course is required to exercise their right by way of the online hiring system. Also see: What is Right of First Refusal (RoFR)?
A Sessional Lecturer Currently Holds a Right of First Refusal for this Course: 
No
Course Details
Course Number: 
UNIV*6080
Course Name: 
Computational Thinking for Artificial Intelligence
Course Format: 
E-Learning (Online Asynchronous)
Course Description: 
See Course Calendar
Other Course Description or Assignment Information: 
TBD
Projected Class Enrolment: 
25
Anticipated Duties and Responsibilities
Anticipated Duties and Responsibilities: 
Orientation-Training
Office Hours
Preparation
Student Consultation
Email Correspondence/Monitoring
Grading
Other Duties Described: 
Monitoring a class discussion board centered around weekly readings, posting comments to spur discussion and answering student questions. If there are any students in the course who do not complete a major final assessment (e.g., final project or final exam), you are required to assign a grade of INC and to provide a deferred assessment with detailed grading scheme to the department before the end of your contract.
Qualifications
Required Qualifications
Degree: 
Masters and Thesis in course content
Prior Teaching Experience: 
No teaching experience required
Minimum TA experience in similar course
Required competence, capability, skill and ability related to course content: 
The successful candidate will have a minimum of a PhD degree in Mathematics, Statistics, Computer Science, Data Science, Computer Engineering or related science or engineering discipline. Successful completion of ENGG*6500 or equivalent course during an engineering undergraduate or graduate degree or demonstrated teaching experience in an equivalent course.
Preferred Qualifications
Degree: 
PhD related to field
Prior Teaching Experience: 
Successful teaching related to field at college or university level.
Research Experience: 
Quality and or Recent Research activity in areas relevant to the course demonstrating knowledge of current developments in course content.
Specific Preferred competence, capability, skill and ability related to course content: 
The successful candidate will preferably have a Ph.D. degree in Mathematics, Statistics, Computer Science, Data Science, Computer Engineering or related science or engineering discipline. The candidate will be extremely familiar with the computational and mathematical underpinnings of Machine Learning.
Days Required and Wages
Days and Times Required: 
TBD
Period of the Work Agreement (Start Date and End Date): 
September 2, 2025 to December 19, 2025
Wages (per semester, per full-load): 
minimum $8,838.51 (effective 2025/26)
Other Posting Information
Application Deadline (All postings will automatically expire at 11:59 pm on this day): 
Thursday, August 14, 2025
Posting Email Contact: 
soe3913@uoguelph.ca
Hiring Contact Information: 
Ibrahim Deiab, Associate Dean Research and Graduate Studies, ideiab@uoguelph.ca, 519-824-4120 ext. 58391, RICH 2521

At the University of Guelph, fostering a culture of inclusion is an institutional imperative. The University invites and encourages applications from all qualified individuals, including from groups that are traditionally underrepresented in employment, who may contribute to further diversification of our Institution. For more information, the Office of Diversity and Human Rights (DHR) is a welcoming, safe and confidential one-stop shop for information, training and support on issues relating to diversity and human rights on our campus.
SL work assignments are unionized with CUPE3913 and their terms and conditions of work are covered by the Unit 2 Collective Agreement between the University and CUPE 3913 (email contact: president@cupe3913.on.ca).

All applicants must be eligible to work in Canada specifically at the University of Guelph before applying for an academic work assignment. All successful applicants must perform their work in Ontario and must be able to attend on-campus in-person meetings as required.