Job Description

Date Posted: 07/21/2026
Req ID: 49472
Faculty/Division: Faculty of Arts & Science
Department: Dept of Economics
Campus: St. George (Downtown Toronto)
Existing Vacancy: Yes

Course Number and Title:

MMF2021H1F: Numerical Methods for Finance (Section LEC 0101)

Course Description:
This course provides a rigorous introduction to numerical methods essential for modern quantitative finance. Students will master key techniques, including finite difference methods for solving partial differential equations arising in option pricing, Monte Carlo simulation and variance reduction techniques for pricing complex derivatives and risk measurement, numerical optimization algorithms for portfolio optimization and calibration of financial models. We will focus on practical applications to real-world problems in derivatives pricing, risk management, and algorithmic trading. Through theoretical lectures, coding assignments, and case studies, students will develop the ability to select, implement, and validate appropriate numerical methods for quantitative finance challenges.

Estimated course enrolment 30

Estimated TA support n/a

Class Schedule Class Schedule: Wednesday 5:00-8:00 pm

The delivery method for this course is in-person.

Sessional dates of appointment September 9 – November 4, 2026

Salary (per section):

$4,998.74 Sessional Lecturer I

$5,349.61 Sessional Lecturer I - Long Term

$5,349.61 Sessional Lecturer II

$5,476.98 Sessional Lecturer II - Long Term

$5,476.98 Sessional Lecturer III

$5,614.45 Sessional Lecturer III - Long Term

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

Minimum qualifications:

• Advanced degree in Mathematical Finance
• Industry experience in partial differential equations, pricing options and complex derivatives
• Prior experience teaching this course (or a similar course) at the university level
• Ability and experience teaching large classes
  
  

Preferred qualifications:

• Industry experience in numerical optimization algorithms and portfolio optimization
  
  

of duties

• 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
  
  

Application instructions:

Applicants should submit an updated curriculum vitae; names and contact information (email and phone) for two referees or two reference letters; evidence of teaching in the relevant area, including student evaluations if available; and the CUPE 3902 Unit 3 application form located here: https://www.economics.utoronto.ca/index.php/index/recruiting/sessionalOpeningsForm

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

Closing Date: 08/14/2026, 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.