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Sessional Lecturer – Neural Networks and Deep Learning

University of Toronto - Woodsworth College · Toronto et périphérie

🇬🇧 English
Neural Networks Deep Learning Recurrent Neural Networks Automatic Differentiation

Job description

About the role

The University of Toronto Mississauga is seeking a sessional lecturer to teach CSC413H5S – Neural Networks and Deep Learning for the Spring 2027 term. The appointment runs from January 1 to April 30, 2027 and includes both lecture and practical sessions.

Key responsibilities

  • Develop and deliver weekly lectures and practical sessions.
  • Prepare tutorials, assignments, tests, and marking schemes.
  • Maintain the course website and provide student support through office hours and online communication.
  • Write TA contracts, supervise teaching assistants, and oversee grading processes.
  • Invigilate the final exam, manage grade submission, and handle student petitions or make‑up exams.

Required profile

  • Graduate degree in Computer Science or Education.
  • Demonstrated advanced knowledge of neural networks and deep learning 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

What we offer

  • Sessional appointment with a competitive salary (rates up to $16,080 for Sessional Lecturer II).
  • TA support of 54 hours per 30 students.
  • Opportunity to teach a cutting‑edge AI course at a leading university.

Questions fréquentes

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Published 2 months ago

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University of Toronto - Woodsworth College

Toronto et périphérie