School of Computer Science Teaching Assistant Positions Winter 2025

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Hiring Unit School of Computer Science
     
Course Title and Course Number

Course Number: COMP 189 – Computer and Society

Course Number: COMP 202 – Course Title: Foundations of Programming

Course Number: COMP 204 – Course Title: Computer Programming for Life Sciences

Course Number: COMP 206 – Course Title: Introduction to Software Systems

Course Number: COMP 208 – Course Title: Computer Programming for Physical Sciences and Engineering

Course Number: COMP 250 – Course Title: Introduction to Computer Science

Course Number: COMP 251 – Course Title: Algorithms and Data Structures

Course Number: COMP 273 – Course Title: Intro to Computer Systems

Course Number: COMP 302 – Course Title: Programming Languages & Paradigms

Course Number: COMP 303 – Course Title: Software Design

Course Number: COMP 310 – Course Title: Operating Systems

Course Number: COMP 322 – Course Title: Introduction to C++

Course Number: COMP 330 – Course Title: Theory of Computation

Course Number: COMP 345 – Course Title: From Natural Language to Data Science

Course Number: COMP 360 – Course Title: Algorithm Design

Course Number: COMP 361D2 – Course Title: Software Engineering Project

Course Number COMP 409 – Course Title: Concurrent Programming

Course Number: COMP 421 – Course Title: Database Systems

Course Number: COMP 511 – Course Title: Network Science

Course Number: COMP 520 – Course Title: Compiler Design

Course Number: COMP 523 – Course Title: Language-based Security

Course Number: COMP 527 – Course Title: Logic and Computation

Course Number: COMP 532- Course Title: Propositional Proof Complexity

Course Number: COMP 535- Course Title: Computer Networks 1

Course Number: COMP 540- Course Title: Matrix Computations

Course Number: COMP 546- Course Title: Computational Perception

Course Number: COMP 549- Course Title: Brain-inspired Artificial Intelligence

Course Number: COMP 551- Course Title: Applied Machine Learning

Course Number: COMP 579 – Course Title: Reinforcement Learning

Course Number: COMP 588 – Course Title: Probabilistic Graphical Models

Course Number: COMP 596- Couse Title: Topics in CS: Cloud Computing

Course Number: COMP 597- Couse Title: Topics in CS: Inclusive Technology Design

Course Number: COMP 598 section 001- Couse Title: Topics in CS: Responsible AI

Course Number: COMP 598 section 002- Couse Title: Topics in CS: Multilingual Representation Learning

Course Number: COMP 599 section 001- Couse Title: Multi-agent Robotics

Position postings can be viewed at: www.cs.mcgill.ca/academic/ta/

Hours of work (per term): 90    

Required duties:
•    – effectively and timely communicate with the instructor and the students;
•    – maintain and observe office and/or lab hours;
•    – develop grading scripts to be used to grade assignments and/or exams;
•    – grade assignments and exams under the supervision of the instructor;
•    – monitor the discussion board/emails;
•    – prepare solution sets for assignments, etc.;
•    – supervise students during midterm evaluations and/or quizzes;
•    – use software for plagiarism detection and verify similarities in the students’ work;
•    – be available throughout the examination period;
•    – photo copy course notes, hand outs, etc.;
•    – ensure confidentiality regarding course-related matters;
•    – respect and treat all students equally.

Qualifications Required:

Positions are for McGill Registered students only.

Must have command of the course material and must be able to demonstrate this command to the satisfaction of the course instructor. At the very least, should be capable of doing the homework assigned to the students in the course. Must be willing to interact with students in the lab.  Must also have good command
English language and must possess good communication skills.

Name & Title of Immediate Supervisor: Various

Dept. Authorization: M. Blanchette

 Date: October 4, 2023

NOTES: 

These positions are open to McGill Registered Graduate students only.
    Announcements are considered tentative, pending final determination of course offerings and enrolments. 

McGill University is committed to equity and diversity within its community and values academic rigour and excellence. We welcome and encourage applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to engage productively with diverse communities.

At McGill, research that reflects diverse intellectual traditions, methodologies, and modes of dissemination and translation is valued and encouraged. Candidates are invited to demonstrate their research impact both within and across academic disciplines and in other sectors, such as government, communities, or industry.

McGill further recognizes and fairly considers the impact of leaves (e.g., family care or health-related) that may contribute to career interruptions or slowdowns. Candidates are encouraged to signal any leave that affected productivity, or that may have had an effect on their career path. This information will be considered to ensure the equitable assessment of the candidate’s record.

McGill implements an employment equity program and encourages members of designated equity groups to self-identify. It further seeks to ensure the equitable treatment and full inclusion of persons with disabilities by striving for the implementation of universal design principles transversally, across all facets of the University community, and through accommodation policies and procedures. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence, accessibilityrequest.hr@mcgill.ca.

All qualified applicants are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadians and permanent residents will be given priority.