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Internship Numerical Methods Jobs in Toronto, ON

Wand

Product Data Analyst

Toronto, ON · Remote

$145K - $175K/yr

When a number moves, you'll know before anyone else -- and you'll know why. You'll build in Hex ... Causal inference methods (diff-in-diff, regression discontinuity, propensity matching) * Prior work ...

Omers

Analyst, Total Plan Risk Management

Toronto, ON

CA$86K - CA$130K/yr

Previous experience (including co/op or internship) in capital markets, pensions and/or risk ... Hands-on experience working with large datasets using numerical computing tools, with a desire to ...

All JobsNumerical Methods JobsInternship Numerical Methods JobsInternship Numerical Methods Jobs in Toronto, ON

Internship Numerical Methods information

What are the key skills and qualifications needed to thrive as an intern in Numerical Methods, and why are they important?

To thrive as an intern in Numerical Methods, you need a solid understanding of mathematics, computational modeling, and problem-solving, typically supported by coursework in applied mathematics, engineering, or computer science. Familiarity with programming languages like Python or MATLAB and exposure to numerical analysis software are often expected. Strong analytical thinking, attention to detail, and effective communication help interns interpret results and collaborate with team members. These skills are crucial for accurately solving complex numerical problems and contributing to research or engineering projects.

What is the difference between Internship Numerical Methods vs Data Analyst?

AspectInternship Numerical MethodsData Analyst
Required CredentialsBasic knowledge of mathematics, programming, and numerical algorithmsBachelor's degree in statistics, mathematics, or related field
Work EnvironmentInternship setting, often in research or technical teamsOffice environment, working with data sets and reporting tools
Employer & Industry UsageResearch institutions, engineering firms, tech companiesBusiness, finance, healthcare, marketing sectors
Search & Comparison IntentUnderstanding entry-level roles in numerical computationExploring data analysis careers and skills

Internship Numerical Methods focuses on applying mathematical and computational techniques to solve problems, often in research or technical settings. Data Analyst roles involve interpreting data, creating reports, and supporting decision-making in various industries. While both require analytical skills, internships emphasize learning and applying numerical algorithms, whereas data analysts focus on data interpretation and visualization.

What are internship numerical methods?

Internship numerical methods refer to internships focused on applying mathematical techniques and algorithms to solve real-world problems using numerical computations. These internships typically involve working with numerical analysis, modeling, simulation, and programming to analyze data or solve engineering and scientific problems. Interns may use tools like MATLAB, Python, or specialized software to implement and test numerical algorithms under the guidance of professionals. Such internships are valuable for students in mathematics, engineering, physics, or computer science, offering practical experience in computational problem-solving.

What types of projects can an intern expect to work on during a Numerical Methods internship?

As a Numerical Methods intern, you can expect to work on projects involving the development, implementation, and testing of algorithms for solving mathematical problems—such as differential equations, optimization, or data analysis tasks. You may collaborate with engineers or researchers to improve computational models, validate results, or optimize code for efficiency. These projects often require a mix of programming (commonly in Python, MATLAB, or C++), mathematical analysis, and teamwork. This hands-on experience is valuable for building problem-solving skills and gaining exposure to real-world applications of numerical techniques.
What are popular job titles related to Internship Numerical Methods jobs in Toronto, ON? For Internship Numerical Methods jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Internship Numerical Methods jobs in Toronto, ON look for? The top searched job categories for Internship Numerical Methods jobs in Toronto, ON are:
Internship Numerical Methods jobs near you
Infographic showing various Internship Numerical Methods job openings in Toronto, ON as of July 2026, with employment types broken down into 2% Internship, 76% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.
Sessional Lecturer - CSC2703HY - Handling an Internship Offer module

Sessional Lecturer - CSC2703HY - Handling an Internship Offer module

University of Toronto

Toronto, ON • On-site

CA$2.1K/wk

Other

Posted 3 days ago

Job description

Date Posted: 06/26/2026
Req ID: 49084
Faculty/Division: Faculty of Arts & Science
Department: Department of Computer Science
Campus: St. George (Downtown Toronto)

Description:

Course number and title: CSC2703HY, LEC5101- Technical Entrepreneurship - Handling an Internship Offer, 0.1 FCE.

*Please note, this is a 0.5 FCE course co-taught with a faculty member; the hired Sessional Lecturer will teach modules equivalent to 0.1 FCE (or 20% of the section).   

Course description: The MScAc degree is intended to create technical leaders capable of transferring new ideas and technologies from academia to industry.  This course introduces fundamental concepts from business and management that are relevant to students thinking about starting their own business or bringing new ideas to fruition within existing ones.  This course will also equip students with practical experience of presenting and defending their scientific research through various research activities and communications.

Estimated course enrolment: maximum 120 students per section

Estimated TA support:  To be determined in consultation with the instructor

Class schedule: LEC5101 biweekly on Wednesdays 6:00pm-9:00pm (in-person);  

*Please note, the delivery method for this course is offered in-person and online - synchronous. Please note that, in keeping with current circumstances, the course delivery method may change as determined by the Faculty or the Department.   

Sessional dates of appointment: Winter session (January 1, 2027-April 30, 2027), however this appointment is only for February 9, 2027-March 6, 2027

Salary:

Sessional Lecturer I = $1,999.50; 

Sessional Lecturer I - Long Term = $2,139.84; 

Sessional Lecturer II = $2,139.84; 

Sessional Lecturer II - Long Term = $2,190.79; 

Sessional Lecturer III = $2,190.79; 

Sessional Lecturer III - Long Term = $2,245.78;

The work the sessional will complete for each section of this course is equivalent to a 0.1 FCE load and thus the salary has been prorated here.

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:

  • Graduate degree in a STEM or relevant field required.
  • Demonstrated superior communication skills required.
  • Strong organizational and interpersonal skills required.
  • Demonstrated experience and evidence of teaching scientific communication methods, including writing, public speaking and interpersonal communications to students with advanced backgrounds in STEM subjects.

Preferred qualifications:

  • Demonstrated evidence of extensive experience in a technology company or technology and innovation focused environment preferred.
  • Demonstrated evidence of experience in progressively senior leadership roles within companies, preferably in roles that have involved hiring and negotiating internship offers.
  • Demonstrated evidence of excellence in teaching preferred.

Description of duties:

  • Planning the lectures, tutorials, assignments, tests, and marking schemes associated with the module.
  • Maintaining a module website.
  • Delivering module material.
  • Providing appropriate contact time outside of class to students, through office hours, email, the module website and/or the module e-bulletin board.
  • Assisting with preparing the breakdown of TA hours and supervising the TA(s) (if applicable).
  • Managing the assessment of the module and invigilating the final exam (if applicable).
  • Managing and submitting all module grades, including the timely completion and release of grades and feedback to students throughout the term.

While there is a lot of room for creativity in course delivery, instructors will be expected to follow the basic content and style used by the faculty members who normally teach the course, and must get approval from these faculty members or from the Academic Director, Professional Programs for any substantial changes to the module content or assessment methods. Instructors will also be expected to consult with the MScAC Program Team when creating the syllabus, assignments, and final exam/test(s).

Application instructions: All individuals interested in this position must submit their application by using the following form. (Direct link:https://forms.office.com/r/CrtNHZm5fw. This includes submitting an updated Curriculum Vitae and the CUPE 3902 Unit 3 application form available at https://uoft.me/CUPE-3902-Unit-3-Application-Form.  

Questions on the application form also include:

  • asking for a clear description of how you meet the qualifications listed.
  • providing the name of at least one reference who can comment on your teaching ability.
  • identifying if you are interested in applying for one this section.

If you have any questions, please email: sessional_lecturer@cs.toronto.edu.

***

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 email: sessional_lecturer@cs.toronto.edu.

Closing Date: 07/23/2026, 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.

Candidates who are members of Indigenous, Black, racialized and 2SLGBTQ+ communities, persons with disabilities, and other equity-deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the position.

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