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University of Toronto

Sessional Lecturer - CSC367H1S - Parallel Programming

Toronto, ON, Canada

Apply by: Oct 21, 2026
Posting language: English
Posted: Sep 28, 2026

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Original job description

Date Posted: 09/28/2026
Req ID: 50307
Faculty/Division: Faculty of Arts & Science
Department: Dept of Computer Science
Campus: St. George (Downtown Toronto)

Description:

Course number and title: CSC367H1S - Parallel Programming

Position 1: CSC367H1S, LEC0101 Position 2: CSC367H1S, LEC0201

Please note, this position is a 0.5 FCE appointment.

Course description: Introduction to aspects of parallel programming. Topics include computer instruction execution, instruction-level parallelism, memory system performance, task and data parallelism, parallel models (shared memory, message passing), synchronization, scalability and Amdahl's law, Flynn taxonomy, vector processing and parallel computing architectures.

Reference: https://artsci.calendar.utoronto.ca/course/csc367h1

Estimated course enrolment: 125 students per section

Estimated TA support: one 60-hour TA position for every 30 students

Class schedule:

Position 1: Mondays, Wednesdays, and Fridays 10:00-11:00 Position 2: Mondays, Wednesdays, and Fridays 10:00-11:00

*Please note, the delivery method for this course is currently in-person. Please note that, in keeping with current circumstances, the section delivery method may change as determined by the Faculty or the Department.

Sessional dates of appointment: January 1, 2027 – April 30, 2027

Salary:

Sessional Lecturer I = $9,997.48

Sessional Lecturer I - Long Term = $10,699.22

Sessional Lecturer II = $10,699.22

Sessional Lecturer II - Long Term = $10,953.96

Sessional Lecturer III = $10,953.96

Sessional Lecturer III - Long Term = $11,228.90

Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Minimum qualifications:

Graduate degree in Computer Science or closely related field required.
Demonstrated expertise in topic area of the course required.
Strong organizational, interpersonal, and communication skills required.
Teaching experience at the university level or equivalent industry level required.

Preferred qualifications:

Previous experience teaching undergraduate courses in the field of Computer Science preferred.
Demonstrated evidence of excellence in teaching preferred.

Description of duties:

Preparing and delivering the lectures in-person on campus as scheduled.
Handling course administration including: maintaining the course website on Quercus; developing marking schemes/syllabus; planning tutorial content (when applicable); developing course assessments including assignments, projects, quizzes, tests, and final assessments.
Providing appropriate contact time outside of class to students, through office hours, email, the course website and/or the course bulletin board.
Preparing the breakdown of hours for TA duties in the course and supervising the TAs.
Ensuring that tutorials and/or labs are delivered appropriately by the TAs as applicable.
Managing the grading for the course, which is largely done by the TAs, and carrying out any grading not handled by the TAs.
Invigilating term tests and the final exam when applicable.
Managing the grades, including the timely completion and release of grades and feedback to students throughout the term; submitting final course grades (due May 7, 2027).

While there is a lot of room for creativity in course delivery, instructors will be expected to follow the basic content and style used by the faculty members who normally teach the course, and must get approval from these faculty members or from the Associate Chair for any substantial changes to the course content or assessment methods. Instructors will also be expected to consult with the department’s Teaching Support group when creating the course syllabus and course assessments (tests, assignments, projects, and final exam)

Application instructions: All individuals interested in this position must submit their application by using the following application form . The direct link is: https://forms.cloud.microsoft/r/2TuHwFsjtq. This includes submitting an updated Curriculum Vitae and the CUPE 3902 Unit 3 application form available at https://uoft.me/CUPE-3902-Unit-3-Application-Form. If you have any questions, please email: sessional_lecturer@cs.toronto.edu.

***

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please email: sessional_lecturer@cs.toronto.edu.

Closing Date: 10/20/2026, 11:59PM EDT
**

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.

It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.

Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.

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More about this job

Responsibilities

Prepare and deliver in-person lectures, administer the course, develop assessments, and provide student support. Supervise teaching assistants, manage grading and course grades, and coordinate course materials and assessment plans with faculty and the department’s Teaching Support group.

Requirements

A graduate degree in Computer Science or a closely related field, demonstrated expertise in the course subject, strong organizational, interpersonal, and communication skills, and university-level or equivalent industry teaching experience are required. Previous undergraduate Computer Science teaching experience and evidence of teaching excellence are preferred.

Skills

Parallel Programming
Computer Science
Instruction-Level Parallelism
Memory System Performance
Task and Data Parallelism
Shared-Memory Programming
Message Passing
Synchronization
Scalability
Amdahl's Law
Vector Processing
Parallel Computing Architectures
University-Level Teaching
Course Administration
Assessment Development
Teaching Assistant Supervision

Visa sponsorship

Not detected in the job text

Keywords

Parallel Programming
Computer Science
Instruction Execution
Instruction-Level Parallelism
Memory System Performance
Task Parallelism
Data Parallelism
Shared Memory
Message Passing
Synchronization
Scalability
Amdahl's Law
Flynn Taxonomy
Vector Processing
Parallel Computing Architectures
Quercus
Course Administration
Syllabus Development
Assessment Development
Assignments
Projects
Quizzes
Tests
Final Exam
Teaching Assistant Supervision
Grading
In-Person Lectures

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