TA221200- Fall 2022-CIS*6030 Information Systems

Teaching Assistant Work Assignment
Posting Details
Type of Work Assignment and Bargaining Unit: 
GTA, Unit 1
Academic Unit: 
School of Computer Science
Semester(s) of Assignment(s): 
Fall 2022
This Work Assignment(s) may be assigned to fulfill the terms and conditions of a guaranteed Job Security Period: 
Yes
Course Details
Course Number: 
CIS*6030
Course Name: 
Information Systems
Course Format: 
In-Class
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. IMPORTANT NOTE REGARDING WORK ASSIGNMENTS AND COURSE DELIVERY IN OUR FALL RETURN-TO-CAMPUS PLANNING. The University will be offering a significant portion of its courses face-to-face “In-Class”. Remote and alternative delivery modes will also occur. Should conditions change and requirements are placed on the University and its employees by public health bodies, local, provincial, and federal governments, courses posted as ‘In-Class’ may have to switch to an alternative delivery format (see https://opened.uoguelph.ca/academic-continuity). By accepting this contract, you are agreeing to fulfill the duties in the mode of delivery posted and switch as required. Should you require a medical accommodation, please notify your supervisor immediately. * Course format: When applying for this work assignment, please be aware that the course is being delivered in a format conducive to the current guidance of the provincial and federal government. Courses offered in-class may be required to pivot to alternate delivery format in the case that requirements placed on the University and its employees by public health bodies, local, provincial and federal governments necessitate such a mid-semester transition. Should this occur, TAs will be required to continue to support the course in its alternate format. * Location/Availability: Work location will vary based on current guidance. Applicants must be aware of this and available to support a course in formats such as: Distance Education, in-person, or alternative delivery format. At the time of this posting, the guidance from provincial and federal bodies indicates an alternative or DE format is likely. Applicants should indicate their availability for each scenario, if possible. * Should conditions change and requirements are placed on the University and its employees by public health bodies, local, provincial, and federal governments, courses posted as ‘In-Class’ may have to switch to an alternative delivery format (see https://opened.uoguelph.ca/academic-continuity). By applying to this work assignment, you are agreeing to fulfill the duties in the mode of delivery posted and switch as required. The University’s COVID-19 website(https://www.uoguelph.ca/covid19/) provides important information about campus protocols and guidelines for those working on campus.
Projected Class Enrolment: 
20
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 0.5 (70 hour) Work Assignments: 
1
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: 
1
Duties and Responsibilities
Anticipated Duties and Responsibilities: 
Office Hours
Preparation
Student Consultation
Email Correspondence/Monitoring
Conducting Labs/Seminars
Meetings
Grading
Qualifications
Required Qualifications: 
• As per the Collective Agreement, must be enrolled as a student in the Fall 2022 semester. • Must have excellent writing skills and be able to effectively critique student assignments in writing. • The ability to communicate computer science concepts to students effectively, both in written form and verbally. • Normally, the completion of an undergraduate degree in Computer Science. • An advanced and documented knowledge of machine learning that includes unsupervised, supervised, and deep learning.
Preferred Qualifications: 
• Previous successful TA experience supporting CIS*4510 (Computer Security Foundations) or CIS*6030 (Information Systems). • An advanced and documented knowledge of machine learning that includes unsupervised, supervised, and deep learning. • Have completed CIS*4510 (Computer Security Foundations), CIS*6030 (Information Systems), or CIS*6510 (Cybersecurity and Defence-in-Depth) or a similar course with a minimum grade of 80%.
Days Required and Wages
Days and Times Required: 
Times required are anticipated to be primarily be centred around North American standard timezones when students are most active. This applies to other student-TA interactions, such as office hours, coordinating with the instructor, etc.; however, times will vary based on student activity.
Period of the Work Assignment (Start Date and End Date): 
September 6, 2022 to December 23, 2022
Wage Rate (per hour, per semester, per Full-load 1.0 Work Assignment): 
GTA $43.73/hr; $6125.96/semester effective 2022/23
Other Posting Information
Application Deadline (All postings will automatically expire at 11:59 pm on this day): 
Friday, July 8, 2022
Posting Email Contact: 
socspost@uoguelph.ca
Hiring Contact Information: 
Joshua Lange Instructional Support Coordinator jlange@uoguelph.ca

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.