Image Processing and Vision
for Teaching Assistants, Graduates Service Assistants & Sessional Lecturers
TA400763- Winter 2027-CIS
* 4720 Image Processing and Vision
Teaching Assistant Work Assignment
Type of Work Assignment and Bargaining Unit:
GTA, Unit 1
Academic Unit:
School of Computer Science
Semester(s) of Assignment(s):
Winter 2027
This Work Assignment(s) may be assigned to fulfill the terms and conditions of a guaranteed Job Security Period:
Yes
Course Number:
CIS
* 4720
Course Name:
Image Processing and Vision
Course Format:
In-Person
Course
Description:
See Course Calendar
Other Course Description or Assignment Information:
The total number of assignments is a low estimate of the number of available appointments. The final number may be higher and it will depend on class enrolment at the time of assignment.
90
Level of Appointment for GTA, GSA-1 UTA(s)
The following is an estimate of number and levels of available appointments at the time of posting. This may change (increase or decrease) at the time of assignment contingent on departmental needs.
This Posting includes Multiple Work Assignments:Yes
Number of Available 0.25 (35 hour) Work Assignments:0
Number of Available 0.5 (70 hour) Work Assignments:0
Number of Available 0.75 (105 hour) Work Assignments:0
Number of Available Full 1.0 (140 hour) Work Assignments:1
Total Number (Load) of Assignment(s) Available:1
Duties and Responsibilities- Orientation-Training
- Office Hours
- Preparation
- Student Consultation
- Conducting Labs/Seminars
- Meetings
- Invigilating Exams
- Grading
Other Duties Described:
Marking assignments and returning them to students on time. Collaborating and mentoring.
NOTICE:
The use of AI to perform job responsibilities must be directed by or approved beforehand in writing by the supervisor or course instructor.
Required Qualifications:
- Must be enrolled as a student in Winter 2027 and able to complete in-person responsibilities.
- Knowledge of fundamental matrix and vector operations, such as matrix/matrix and matrix/vector multiplication, matrix inverse and transpose, the dot product, etc.
- Background in Computer Science.
- A thorough understanding of programming.
- The ability to communicate mathematical and computer science concepts to students effectively, both verbally and in writing.
- Passed CIS
* 4720 (Image Processing and Vision) or similar course, with a minimum grade of 75%. - Previous successful TA experience supporting this course.
- Has previous experience preparing and teaching labs.
- Experience using mathematical concepts in a higher-level programming language, such as Python, Julia, or Matlab.
Days and Times
Required:
See duties and qualifications above, as well as Web Advisor for lecture and lab days and times. Should be able to attend labs (Wednesdays 4:30pm-5:20pm). Must be available to complete TA duties as required until the end of the work period (May 7th, 2027).
Period of the Work Assignment (Start Date and End Date):
January 7, 2027 to May 7, 2027
Wage Rate (per hour, per semester, per Full-load 1.0 Work Assignment):
Other Posting InformationFinal date to receive applications (All postings will automatically expire at 11:59 pm on this day):
Thursday, November 12, 2026
Posting Email Contact:
Hiring Contact Information:
Instructional Support Coordinator - teac
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.
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.
Teaching Assistant work assignments are unionized with CUPE 3913 and their terms and conditions of work are covered by the Unit 1 Collective Agreement between the University and CUPE 3913 (email contact: ).
The use of AI to perform job responsibilities must be directed by or approved beforehand in writing by the supervisor or course instructor.
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