Sessional Lecturer - MMF: Information Technology; Section LEC

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Date Posted: 07/07/2026
Req : 49182
Faculty/Division: Faculty of Arts & Science
Department: Dept of Economics
Campus: St. George (Downtown Toronto)
Existing Vacancy: Yes

Course Number and

Title:

Course

Description:

This course provides an introduction to information technology and financial data in the context of modern finance. Students will learn the foundations of Natural Language Processing (NLP) and how it applies to building financial datasets. The course will cover classification models like Softmax Regression, neural networks, and Multilayer Perceptrons. Students will gain practical experience with Python and PyTorch, learning about vector lookups and embeddings, and self‑attention.

The course will also introduce students to cutting‑edge topics like BERT, causal Large Language Models (LLMs) for text continuation, and Reinforcement Learning from the basics to GRPO – the technique used to train Deep Seek‑R1.

The delivery method for this course is in‑person.

August 18-21, 2026

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

• Advanced degree in computational mathematics
• Industry experience in NLP, neural networks, multilayer perceptrons, and classification models
• Prior experience teaching this course (or a similar course) at the university level
• Ability and experience teaching large classes

• Industry experience in information technology and financial data in the context of modern finance

• Preparation and delivery of lectures in this course
• Preparation, supervision and grading of tests and examinations in accordance with university regulations
• Providing scheduled office hours for academic counseling of students

Please attach the additional documents in one PDF file format to the application form. If you have any questions, please contact ses All applicants must have a valid email address.

07/15/2026, 11:59 PM 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. 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.

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.

The University of Toronto embraces diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see (Use the "Apply for this Job" box below)..

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission. 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 contact