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Vector Institute

Vector Distinguished Postdoctoral Fellow

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Job type: Full-time
Apply by: Nov 1, 2026
Posting language: English
Posted: Oct 2, 2026

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Original job description

Position Overview

Are you an early career researcher with the potential to become a world-class machine learning scientist? The Vector Institute invites applications for Distinguished Postdoctoral Fellows who are working on cutting-edge fundamental research in machine learning and deep learning algorithms and their applications.

Our Areas Of Research Include

Computer Vision
Generative Models
Healthcare – computational biology, genomics
Natural Language Processing
Optimization
Reinforcement Learning
Statistical Learning Theory
Sequential Decision Making
Security, Privacy & Fairness
Quantum Computing

The standard term for a Distinguished Postdoctoral Fellow position is 1–2 years, with a possible extension to 3 years. Also available is the opportunity for eligible individuals to complete a placement at Vector before going on to take a faculty role elsewhere.

Responsibilities

Distinguished Postdoctoral Fellows at the Vector Institute are early career researchers with the potential to become world-class researchers. Like postdoctoral researchers in a university lab, Distinguished Postdoctoral Fellows at the Vector Institute are tasked with and supported in carrying out state-of-the-art research, publishing at the highest international level, and contributing to the academic life and reputation of the Institute. The Vector Institute offers a dynamic environment, and research freedom and opportunity to collaborate within and across research areas. They are part of a thriving research community of over 860 Vector Faculty Members, Faculty Affiliates, Postgraduate Affiliates, Postdoctoral Fellows, and graduate students.

Distinguished Postdoctoral Fellows at the Vector Institute have access to the resources of a well-funded institute dedicated solely to machine learning and deep learning, and are encouraged to work with any of our over-45 world-class faculty in machine learning and deep learning, though they will work primarily with 1–2 faculty members.

They will be expected to propose work on research topics of their interest related to machine learning and deep learning and carry out that research with a great deal of independence. Should they be so inclined, Distinguished Postdoctoral Fellows may teach and mentor at the Institute; engage in entrepreneurial activities; and/or work with existing companies to enhance their research. They have the ability to collaborate with the graduate students of the machine learning group at the University of Toronto, as well as the graduate students of other affiliated faculty, who spend the bulk of their time at the Institute.

About Vector

The Vector Institute is an independent non-profit corporation, with Faculty Members and Affiliates from the University of Toronto, University of Waterloo, and other Canadian universities. It is supported with generous funding from the provincial and federal governments, as well as Canadian industry sponsors.

The Vector Institute is strategically positioned at the forefront of AI advancement, located on the 11-13th floors of the University of Toronto’s new Schwartz Reisman Innovation Campus, surrounded by leading scholars, entrepreneurs, and industry partners. On any given day, the Vector Institute houses over a hundred students, dozens of Faculty Members, supported with state-of-the-art compute power, and dedicated professional staff. The daily life and concentration of expertise in the Institute fosters collaboration and the exchange of ideas among its members through talks, seminar series, visitors, and tutorials.

The Vector Institute’s vision is to drive excellence in the creation of artificial intelligence, to use it to foster economic growth, and to improve the lives of Canadians. To that end, the Vector Institute has close ties to both academia and industry. This puts our Distinguished Postdoctoral Fellows in a unique position to contribute broadly. A successful contribution can range from developing core algorithmic techniques and theoretical analyses of machine learning algorithms, to working closely with existing companies and health organizations, to engaging in entrepreneurial activities.

In addition to their research, Distinguished Postdoctoral Fellows have the opportunity to work with industry to develop machine-learning-based solutions for their problems or engage in related entrepreneurial activities. We have dedicated staff facilitating all aspects of engaging with Vector sponsors and affiliated institutions, as well as close ties to incubators for entrepreneurial activities. The Vector Institute has extensive access to computing resources and datasets. We have a team of AI Engineers who help improve research productivity through software platform development, ensuring research reproducibility, publishing open source code and data, and in readying code for commercial use.

WHO SHOULD APPLY?

We are looking for people with interests across a broad spectrum from core machine learning or deep learning research to more applied and entrepreneurial activities. We are also looking for people who have excelled in other areas and are interested in moving into deep learning or machine learning more broadly.

The Vector Institute’s research programming, including Vector Postdoctoral Fellowships, is supported by funding made available through the federal Pan-Canadian AI Strategy. As a federally funded program, Vector will not consider applications from researchers who are currently affiliated with, or in receipt of funding or in-kind support* with a Named Research Organization under the federal Policy on Sensitive Technology Research and Affiliations of Concern (STRAC).

Please consult Policy on Sensitive Technology Research and Affiliations of Concern (STRAC) for definitions.

Requirements

PhD or equivalent in Computer Science, Statistics, Electrical Engineering, or a closely related field. You must have completed all requirements of your doctoral degree no more than three years before the application deadline;
An excellent publication record in machine learning;
Expertise in a core area of machine learning, such as deep, unsupervised, and reinforcement learning, optimization, and theory; and/or applied machine learning, such as natural language, health, vision, robotics, medicine, biology, transportation, media, and finance;
For those looking to pivot to machine learning from a field with technical overlap, we are looking for an excellent publication record in your field as well as expertise in an area with some potential relevance to machine learning.

Application Requirements

Please note that all documents have to be converted and merged into a single PDF document and uploaded as one PDF file in your application via ADP .

A cover letter, including identifying a Vector Faculty Member as potential supervisor. We encourage applicants to contact Faculty Members before submitting their application.
A curriculum vitæ.
Links to at least three recent publications.
A research statement outlining a proposed program of research.
Three reference letters. One referee should be your PhD supervisor. If referees prefer to submit reference letters directly, they can be sent to research@vectorinstitute.ai before the application deadline.

DEADLINES

Spring Cohort

To be considered for the Spring Cohort, application and reference letters must be received in full by 23:59 EST on February 28th.

Autumn Cohort

If you wish to be considered for the Autumn Cohort, application and reference letters must be received in full by 23:59 EST on August 31st. Any applications received after this date will be added to the next cohort.

The Hiring Committee reviews applications on a rolling basis twice per year: March and September .

Please submit applications, using the link provided, ensuring all required materials are included in one PDF document .

INTERVIEWS

Please note that all interviews are currently being held remotely.

We thank all applicants for their interest in this exciting opportunity and will be in touch with those whose qualifications most closely match with our needs.

Achieving a more equitable, diverse and inclusive research institute is essential to creating excellent, innovative, and impactful research. The Vector Institute is committed to employment equity and diversity in the workplace and welcomes applications from women, racialized persons/visible minorities, Indigenous peoples, persons with disabilities, and 2SLGBTQIA+ persons. Should you wish to self-identify, please indicate this in your cover letter. All qualified candidates are encouraged to apply.

Further, we are committed to fostering an environment of inclusivity and accessibility. If you require an accommodation at any point throughout the recruitment and selection process, please contact hr@vectorinstitute.ai and we will happily work with you to meet your needs.

Location

Toronto, Ontario

Department

Research

Employment Type

Fellow

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More about this job

Responsibilities

Conduct independent, state-of-the-art research in machine learning and deep learning, publish at a high international level, and contribute to the Vector Institute’s academic community. Fellows may also collaborate with faculty, students, industry, and health organizations, and may participate in teaching, mentoring, or entrepreneurial activities.

Requirements

Applicants must hold a PhD or equivalent in computer science, statistics, electrical engineering, or a closely related field, completed no more than three years before the application deadline. They must have an excellent publication record and expertise in machine learning or a technically relevant field, with research experience in a core or applied area.

Skills

Machine Learning
Deep Learning
Computer Vision
Generative Models
Computational Biology
Genomics
Natural Language Processing
Optimization
Reinforcement Learning
Statistical Learning Theory
Sequential Decision Making
Security
Privacy
Fairness
Quantum Computing
Research

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Deep Learning
Computer Vision
Generative Models
Computational Biology
Genomics
Natural Language Processing
Optimization
Reinforcement Learning
Statistical Learning Theory
Sequential Decision Making
Security
Privacy
Fairness
Quantum Computing
Artificial Intelligence
Research
Research Publications
Algorithm Development
Theoretical Analysis
Healthcare
Robotics
Transportation
Finance
Entrepreneurship
Open-Source Software
Research Reproducibility
Data
Industry Collaboration

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