Sessional Lecturer - APS360H1 S Applied Fundamentals of Deep Learning

Date Posted: 10/25/2024
Req ID: 40398
Faculty/Division: Faculty of Applied Science & Engineering
Department: Cross-Disciplinary Programs Office
Campus: St. George (Downtown Toronto)

Description:

Course title: APS360H1 S – Applied Fundamentals of Deep Learning

Course description: A basic introduction to the history, technology, programming and applications of the fast evolving field of deep learning. Topics to be covered may include neural networks, autoencoders/decoders, recurrent neural networks, natural language processing, and generative adversarial networks. Special attention will be paid to fairness and ethics issues surrounding machine learning. An applied approach will be taken, where students get hands-on exposure to the covered techniques through the use of state-of-the-art machine learning software frameworks.

Estimated enrolment:  1 section with enrolment of 100

Estimated TA support:   300 hrs per section

Course Schedule: Candidates must be available for both sections as scheduled.

LEC0101 - Monday 6-8 p.m./Wednesday 7-9 p.m.

Sessional dates of appointment:  January 1, 2025- April 30, 2025

Stipend: $16,710 (inclusive of vacation pay) per section.

Qualifications: Ph.D. or equivalent professional experience in the area of AI and Machine Learning; P.Eng. preferred. Knowledge of, and experience with deep neural networks and their application to computer vision and other pattern recognition problems is required. Knowledge of forward-looking AI/ML concepts, such as reinforcement learning and recurrent neural networks, preferred. Hands-on experience with PyTorch highly desirable.  Familiarity with fairness and ethics issues surrounding AI. Previous experience teaching a similar course is highly desirable. Familiarity with engineering concepts and engineering education is an asset.     

Duties: The lecturer will prepare for and deliver 13 weeks of lectures and tutorials; set assignments and term work assessments and final assessment as appropriate; collate and submit marks; handle petitions after final marks have been submitted; communicating with students both inside and outside of class times.   Preparation of a deferred examination may also be required.  Delivery of this course is intended to be in-person but may be online or a hybrid as dictated by Public Health guidelines.

Closing Date: November 15, 2024, 11:59 p.m..

Those interested should submit a cover letter, current cv detailing teaching experience, and CUPE 3902 Unit 3 application form by email to:

Sharon Brown
Associate Director

Cross-Disciplinary Programs Office

Faculty of Applied Science and Engineering

email: s.brown@utoronto.ca
 

Closing Date: 11/15/2024, 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.