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Sessional Lecturer - CSCHF LEC; emerg

Job in Toronto, Ontario, C6A, Canada
Listing for: University of Toronto
Seasonal/Temporary position
Listed on 2026-07-21
Job specializations:
  • Education / Teaching
    College Lecturer, University Professor
Salary/Wage Range or Industry Benchmark: 14381 CAD Yearly CAD 14381.00 YEAR
Job Description & How to Apply Below
Position: Sessional Lecturer - CSC413H5F LEC101 (emerg posting)

Course Information

Course Number and

Title:

CSC
413H5F LEC
101 – Neural Networks and Deep Learning

Course

Description:

An introduction to neural networks and deep learning. Back propagation and automatic differentiation. Architectures: convolutional networks and recurrent neural networks. Methods for improving optimization and generalization. Neural networks for unsupervised and reinforcement learning.

Number of Positions: 1

Sessional Dates of Appointment: September 1, 2026 – December 31, 2026

Salary: Rate of pay for Sessional Lecturer is as follows:
Sessional Lecturer I = $14,381;
Sessional Lecturer I - Long Term = $16,080;
Sessional Lecturer II = $16,080.

Responsibilities

Responsible for all aspects of delivering a university credit course including: developing and delivering lectures; preparing tutorials, assignments, tests, and marking schemes; maintaining a course website; providing appropriate contact time outside of class to students through office hours, emails, the course website, and/or the course discussion board; writing the TA contract(s) for the course and supervising the TAs; managing the grading for the course, which is largely done by TAs;

doing any grading not handled by TAs; invigilating the final exam; managing the grades and submitting the final course grades; dealing with student petitions; and setting and grading a make-up exam if required. 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.

Minimum Qualifications
  • Completion of a graduate degree in Computer Science or education.
  • Advanced comprehension of the subject matter as evidenced by research activity, industry experience, or teaching experience.
  • Strong organizational, interpersonal, and communication skills.
Preferred Qualifications
  • Demonstrated evidence of excellence in teaching.
  • Preference will be given to candidates with demonstrable currency and mastery.
Diversity Statement

Candidates who are members of Indigenous, Black, racialized and 2

SLGBTQ+ communities, persons with disabilities, and other equity-deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the position.

Closing Date

07/30/2026, 11:59PM EDT

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