Intro to Manufacturing Process

for Teaching Assistants, Graduates Service Assistants & Sessional Lecturers

TA399168
- Winter 2027-ENGG
* 2180 UTA LAB Intro to Manufacturing Process
Teaching Assistant Work Assignment
Type of Work Assignment and Bargaining Unit:
UTA, Unit 1

Academic Unit:
School of Engineering

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:
N/A

Course Number:
ENGG
* 2180 UTA LAB

Course Name:
Intro to Manufacturing Process

Course Format:
In-Class

Course

Description:

See Course Calendar

Other Course Description or Assignment Information:
UP to six UTAs will be hired based on availability in the class schedule.

Candidates must be available to attend the labs. The supervisor will provide details in the interview.

277

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:
9

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:
0

Total Number (Load) of Assignment(s) Available:
9

Duties and Responsibilities
Anticipated

Duties and Responsibilities:

Student Consultation

Conducting Labs/Seminars

Other Duties (specify below)
Other Duties Described:
Up to Six UTA applicants will be hired. The Instructor will allocate which Labs each applicant will be responsible for.

Other duties will be assigned

Qualifications

Required Qualifications:

Successfully completed ENGG
* 2180 with a grade of at least 65%.Knowledge and hands‑on experience with machining operations, including milling, turning, and drilling.

Knowledge of casting and welding processes.

Machine shop experience, including familiarity with different machine tools, machining processes, and cutting tools.

Knowledge and experience with machine shop safety training, including the yellow and red card system.

Good communication and interpersonal skills.

Successful completion of an interview with the course instructor.

Must submit a copy of class schedule

Preferred Qualifications:

Experience supporting students during hands‑on machine shop or manufacturing laboratory activities.

Experience maintaining and updating trainee or laboratory training records.

Days Required and Wages
Days and Times

Required:

Dr. Deiab will allocate the lab section you will be responsible for

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):
UTA $31.26/hr effective 2025/26

Other Posting Information
Final date to receive applications (All postings will automatically expire at 11:59 pm on this day):
Tuesday, October 20, 2026

Hiring Contact Information:
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.