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 à l'intelligence artificielleCourse Code:
CSI4506ASection:
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:
1Expected Enrolment:
77Work 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:
Français | FrenchRequirements and Nature of Work:
Description du travail:
1. Préparer et tester des Jupyter Notebook sur divers sujets de l'intelligence artificielle. 2. Être disponible pour des heures de consultations hebdomadaires pour aider les étudiants avec leur devoirs (programmation Python). 3. Être disponible durant le semestre en personne et par courriel pour aider les étudiants avec leur projet de IA. 4. Corriger les devoirs. 5. Corriger le projet.
Exigences minimales:
La préférence sera accordée aux candidats qui ont terminé ce cours avec une note de A ou mieux. Une connaissance approfondie de la matière du cours est requise. Voici les thèmes à connaître: recherches heuristiques, problèmes de satisfaction de contraintes, apprentissage machine (naive bayes, réseaux de neurones), représentation des connaissances (réseaux sémantiques), traitement automatique des langues et système de raisonnement (logique). Capacité à résoudre des exercices et à programmer leurs solutions en langage de programmation Python. Être disponible pour des heures de consultation hebdomadaires afin d'aider les étudiants dans leurs devoirs/projets (programmation Python).
Veuillez noter que la méthode d'enseignement sera dispensée : en présentiel.
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
- Deep knowledge of course material: heuristic search, constraint satisfaction problems, machine learning (Naive Bayes, neural networks), knowledge representation (semantic networks), natural language processing, and reasoning/logic.
- Ability to program solutions and assist students in Python.
- Experience preparing and testing Jupyter Notebooks.
- Availability to hold weekly in-person consultation hours and provide email support during the semester.
- Ability to grade assignments and projects.
- Fluency in French (language of work).
- Completed this course with a grade of A or better.
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.
