Sessional Lecturer for Neural Networks & Deep Learning

About the role

The Department of Mathematics and Computer Science at the University of Toronto Mississauga seeks a sessional lecturer to teach CSC413H5F – Neural Networks and Deep Learning for the Fall 2026 term. You will be responsible for delivering lectures and practical sessions to approximately 60 undergraduate students.

Key responsibilities

• Develop and deliver weekly lectures (Tuesday 17:00‑19:00) and practical labs (Friday 9:00‑11:00).
• Design tutorials, assignments, tests, and grading rubrics.
• Maintain the course website and provide timely support through office hours and online communication.
• Write and manage TA contracts, supervise teaching assistants, and oversee their grading work.
• Grade student work not covered by TAs, invigilate the final exam, and submit final grades.
• Handle student petitions and, if needed, create and grade make‑up examinations.

Required profile

• Completion of a graduate degree in Computer Science or Education.
• Advanced knowledge of neural networks and deep learning demonstrated through research, industry experience, or prior teaching.
• Strong organizational, interpersonal, and communication abilities.

Required skills

• Neural Networks
• Deep Learning
• Convolutional Neural Networks
• Recurrent Neural Networks
• Automatic Differentiation
• Optimization techniques for machine learning
• Unsupervised Learning
• Reinforcement Learning

What we offer

• Competitive sessional salary (rates disclosed to successful candidates).
• TA support of 54 hours per 35 students.
• Opportunity to teach at a leading Canadian university.