Posting Reason:
New PositionLocation where work is to be performed:
Main CampusSession:
2026 Fall Semester | Trimestre d'automneFaculty:
Faculté de génie / Faculty of EngineeringUnit:
EECS_STJob Classification:
Teaching Assistant/Demonstrator/Lab Monitor (CUPE)Posting Type:
Cours précis / Specific courseCourse Title:
Introduction to Artificial IntelligenceCourse Code:
CSI4106ASection:
ASupervisor name (if known):
Date Posted (YYYY/MM/DD):
2026/07/03Applications must be received BEFORE (YYYY/MM/DD):
2026/07/17Description of tasks (hours):
Unless specified below, specific allocation of hours to various tasks should be articulated in a description of work negotiated and signed by you and the supervising professor prior to the commencement of work.
Recherche / Research:0Préparation / Preparation:0Contact avec étudiants / Contact with Students:0Correction - Notation / Grading:0Surveillance / Proctoring:0Formation / Training:0Autre / Other:0Number of positions:
4Expected Enrolment:
225Work Start Date:
September 01, 2026Work End Date:
December 31, 2026Total Work Hours:
130Hourly Rate:
AE-RA-Tuteur / TA-RA-Tutor : $31.89 ou/or $50.25 (2024-2025)The academic year starts on September 1 and ends on August 31.
Undergraduate students will be paid at the lower rate; while graduate students will be paid at the higher rate.
These rates do not included vacation pay nor statutory pay.
These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.
Language of Work:
Anglais | EnglishRequirements and Nature of Work:
Nature of Work:
1. Prepare and test Jupyter Python Notebook on diverse topics of Artificial Intelligence. 2. Be available for weekly consultation hours to help students with Python assignments 3. Be available throughout the semester for email/in person help for the students in their AI project. 4. Evaluate the Python assignments. 5. Evaluate the AI project.
Minimum Requirements:
Preference will be given to applicants who have completed this course with a grade of A or better. A thorough knowledge of the course material is required. Here are the topics to know: heuristic searches, constraint satisfaction problems, machine learning (naive bayes, neural networks), knowledge representation (semantic networks), automatic language processing and reasoning system (logic). Ability to solve exercises and program their solutions in Python programming language. Be available for weekly consultation hours to help students with their assignments/projects (Python programming).
Please note that the teaching method will be delivered: in person.
NOTE: le nombre de postes et le nombre d'heures offertes sont tous deux assujettis aux inscriptions finales dans ce cours. Please note that the number of hours offered may varie due to enrolments in that course.
Additional Information and/or Comments:
All University of Ottawa employees are required under provincial law to successfully complete all mandatory legislated training offered by the University. The list of training requirements may be modified by provincial law. If you are invited to continue the selection process, please notify us of any particular adaptive measures you might require. We may consult with the Health and Wellness sector of Human Resources, if needed. Any information you send us will be handled respectfully and in complete confidence.
The hiring process will be governed by the current CUPE 2626 collective agreement; you can click here to find out more.
The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact the academic unit to communicate the accommodation need.
Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 – Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.
Skills Required
- Prepare and test Jupyter Python Notebooks for course topics
- Be available for weekly consultation hours and provide email/in-person help throughout the semester
- Evaluate and grade Python assignments and the AI project
- Thorough knowledge of course material
- Knowledge of heuristic search, constraint satisfaction problems, machine learning (naive bayes, neural networks), semantic networks, natural language processing, and logic-based reasoning
- Ability to solve exercises and program solutions in Python
- Preference for applicants who have completed this course with a grade of A or better
- Ability to work in English and attend in-person teaching duties on Main Campus
What We Do
The University of Ottawa is a bilingual, research-intensive university in Canada that offers a wide range of undergraduate, graduate, and continuing education programs across ten faculties.
