TA169109- Winter 2021-CIS*3700 Introduction to Intelligent 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): 
Winter 2021
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: 
CIS*3700
Course Name: 
Introduction to Intelligent Systems
Course Format: 
Other
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. Due to the dynamic nature of the response to the novel coronavirus moving into the upcoming semester, the following additional requirements and information are imposed: * 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. * Candidates will be required to work remotely, primarily via the University’s CourseLink system, during regular University instructional hours (8:30 AM to 10:00 PM EST), or as required specifically by the teaching duties imposed.
Projected Class Enrolment: 
42
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: 
Orientation-Training
Office Hours
Preparation
Student Consultation
Email Correspondence/Monitoring
Conducting Labs/Seminars
Meetings
Invigilating Exams
Grading
Qualifications
Required Qualifications: 
• As per the Collective Agreement, must be enrolled as a student in the Winter 2021 semester. • Must have excellent writing skills and be able to effectively critique (in writing) student assignments. • The ability to communicate computer science concepts to students effectively, both in written form and verbally. • Must be available to support scheduled lab hours throughout the entire semester, must be available for weekly meetings with the instructor, and must be available to moderate online forums, if applicable, as assigned by the instructor. • Demonstrated knowledge on artificial intelligence and intelligent systems. • Strong Java programming skills • Ability to grade written assignments according to a specified rubric. • Strong organizational and time management skills. • Ability to grade written assignments accourding to a specified rubric. Must have excellent writing skills and be able to effectively critique (in writing) student assignments. • The ability to communicate computer science concepts to students effectively, both in written form and verbally. • Must be able to support labs through pre-recorded videos. • Must be available for regular Microsoft Teams meetings, and for communicating by emails with the instructor on TA duties. • Demonstrated knowledge on artificial intelligence and intelligent systems. • Strong Java programming skills. • Strong organizational and time management skills.
Preferred Qualifications: 
• Previous successful TA experience supporting CIS*3700 (Introduction to Intelligent Systems). • Demonstrated knowledge of CIS*3700 (Introduction to Intelligent Systems) suubject area throguh course development or taking a similar undergraduate or graduate course. This includes search tree and heuristic search, propsitional logic inference by resolution and chaining, decision tree learning, regression and artificial neural networks. • Taken courses requiring significant written assignments (e.g. Senior Design documents, English, history, philosophy courses).
Days Required and Wages
Days and Times Required: 
See qualifications.
Period of the Work Assignment (Start Date and End Date): 
January 7, 2021 to May 4, 2021
Wage Rate (per hour, per semester, per Full-load 1.0 Work Assignment): 
GTA $42.73/hr; $5984.76/semester effective 2020/21
Other Posting Information
Application Deadline (All postings will automatically expire at 11:59 pm on this day): 
Thursday, November 12, 2020
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 reside 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).