TA399215- Winter 2027-UNIV*6020 Applied Agricultural Stats

Teaching Assistant Work Assignment
Posting Details
Type of Work Assignment and Bargaining Unit: 
GTA, Unit 1
Academic Unit: 
Plant Agriculture
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 Details
Course Number: 
UNIV*6020
Course Name: 
Applied Agricultural Stats
Course Format: 
Blended
Course Description: 
See Course Calendar
Projected Class Enrolment: 
85
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: 
No
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: 
1
Number of Available Full 1.0 (140 hour) Work Assignments: 
0
Total Number (Load) of Assignment(s) Available: 
1
Duties and Responsibilities
Anticipated Duties and Responsibilities: 
Office Hours
Preparation
Student Consultation
Attending Lectures
Email Correspondence/Monitoring
Conducting Labs/Seminars
Meetings
Grading
Qualifications
Required Qualifications: 
- Strong background in statistics, including graduate-level coursework and applied statistical analysis of experimental data (e.g., experimental design, ANOVA, mixed models, regression). - Strong proficiency in both R and SAS for data management, statistical analysis, and data visualization.
Preferred Qualifications: 
- Completion of a graduate-level applied statistics course; PLNT*6170, STAT*6950, or UNIV*6020 preferred. - Prior Teaching Assistant experience in a statistics or quantitative-methods course; experience as a TA for UNIV*6020 preferred. - University-level teaching experience involving laboratory or seminar instruction, grading, and student consultation. - Experience presenting research findings at a conference or to a group of peers.
Days Required and Wages
Days and Times Required: 
LEC Mon, Wed, Fri 1:30 AM - 2:20 AM LAB Friday 9:30 PM - 11:30 PM LAB Wednesday 8:30 AM - 10:20 AM
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): 
GTA $49.43/hr; $6,924.98/semester effective 2025/26
Other Posting Information
Application Deadline (All postings will automatically expire at 11:59 pm on this day): 
Monday, November 2, 2026
Posting Email Contact: 
papost@uoguelph.ca
Hiring Contact Information: 
Applications will be accepted by Graduate Program Assistant in Plant Agriculture Hiring Process: https://www.plant.uoguelph.ca/sites/default/files/documents/Plant%20Ag%20-%20GTA%20Hiring%20Process.2019.08.23.pdf Graduate Teaching Assistant (GTA) Hiring Process: https://www.plant.uoguelph.ca/sites/default/files/documents/Plant%20Ag%20-%20GTA%20Hiring%20Process.2019.08.23.pdf

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: president@cupe3913.on.ca).

The use of AI to perform job responsibilities must be directed by or approved beforehand in writing by the supervisor or course instructor.