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Posted 12 days ago

Post-Doctoral Researcher

@ McGill University

Montréal, Quebec

Full-time
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Overview

McGill University is hiring a Postdoctoral Fellow for a one-year full-time contract in Montreal to build a foundation model of human neurotypes by integrating cognitive task data, conversational text and biometric data. The role centres on self-supervised representation learning and multimodal modelling, with a salary of $60,000 per year and an annual deadline of 2026-11-30.

Responsibilities:

  • Develop tokenization and self-supervised learning methods for diverse data streams
  • Train multimodal architectures projecting data into a unified latent space
  • Work with a psychometrics postdoc to separate cognitive variation from measurement error
  • Design rigorous evaluations of robustness, missing modalities and generalization
  • Scrutinize models for bias and collaborate on data preprocessing pipelines

Requirements summary:

  • PhD in machine learning, computer science, computational neuroscience, statistics or related field
  • Proficiency in Python and modern deep learning frameworks
  • Experience with high-performance computing and GPU clusters
  • Strong research background in multimodal modelling and representation learning
  • Preferred: self-supervised learning, NLP, cognitive modelling, privacy-aware methods

Tools & skills

Source and dates

Employer career site / ATS feed · workday

Employer posting date
2026-10-25
First seen by our source
2026-10-20
Source record updated
2026-11-02

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

SeniorityEntry level
DepartmentResearch & science
Hours per week35
Work settingOffice, Laboratory
PositionMostly sitting
Physical demandsphysical low · computer high
LanguagesEnglish
Encouraged to applyIndigenous peoples, Racialized people, Women, People with disabilities, 2SLGBTQ+
EducationDoctorate (required)
Fields of studymachine learning, computer science, computational neuroscience, statistics

Summary and details written by AI from the posting; the employer’s posting is the authority.

McGill University

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Job description

Please refer to the How to Apply for a Job (for External Candidates) job aid for instructions on how to apply.

If you are an active McGill employee (ie: currently in an active contract or position at McGill University), do not apply through this Career Site. Login to your McGill Workday account and apply to this posting using the Find Jobs report (type Find Jobs in the search bar).

Postdoctoral Fellow, Multimodal Machine Learning


Role Overview

The Postdoctoral Fellow will develop techniques to build a foundation model of human neurotypes by integrating cognitive task performance, conversational text, and biometric data. The core challenge is utilizing self-supervised representation learning to construct a continuous latent manifold of individual differences.


Responsibilities

● Develop tokenization techniques and self-supervised learning methods to integrate diverse data streams (cognitive results, text, creative choices, psychometrics).

● Train models utilizing novel multi-modal architectures to project qualitative and quantitative data into a unified latent space.

● Work closely with a psychometrics postdoc to distinguish genuine cognitive variation from measurement error, device effects, and language confounds.

● Design rigorous evaluations focusing on participant-level data separation, model robustness, missing modalities, and generalization.

● Scrutinize models for bias, unsupported sensitive inferences, and stability, ensuring responsible data usage in collaboration with governance bodies.

● Collaborate with software engineers on data preprocessing pipelines and model integration within the game's cloud infrastructure.


Qualifications

● PhD in machine learning, computer science, computational neuroscience, statistics, or a related discipline.

● Proficiency in Python and modern deep learning frameworks.

● Experience with High-performance Computing Infrastructure and GPU clusters.

● Strong research background in multimodal modeling, representation learning, and statistical evaluation of machine learning models.

● Preferred: Experience with self-supervised learning, natural language processing (NLP), cognitive modeling, and privacy-aware methods.


This is a one-year contract, with the possibility of extension.Compensation to be determined based on experience and qualifications.

To apply for this position, please submit the following:

  • A curriculum vitae (CV) detailing your educational background, research experience, and publications.
  • Contact information for at least two academic or professional references.

This position is covered by the AMURE collective agreement: https://www.mcgill.ca/hr/employee-relations/assocs-unions


Before applying, please note that to work at McGill University, you must be both authorized to work in Canada and willing to work in the province of Quebec at the campus where the position is based / located.

McGill University is an English-language university where most teaching and research activities are conducted in the English language, thereby requiring English communication both verbally and in writing.

Annual Salary:

$60,000.00

Hours per Week:

35 (Full time)

Location:

Montreal Neuro.

Supervisor:

Associate Professor

Position Start Date:

2027-01-01

Position End Date:

2027-12-31

Deadline to Apply:

2026-11-30

McGill University hires on the basis of merit and is strongly committed to equity and diversity within its community. We welcome applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities. McGill implements an employment equity program and encourages members of designated groups to self-identify. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence, [email protected].

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