MSc: Connecting behavioural and communication sciences with expression recognition using deep learning models

Project summary

Achieving sustainable health behaviour change is complex, often influenced by ambivalence (simultaneous desires for and against change) and hesitancy (ranging from full acceptance to complete refusal of new behaviours). These kinds of expressions can be detected through speech patterns and non-verbal cues. In healthcare settings, how clinicians react to these cues can influence patients’ behaviour change.

This project connects these two related issues:

  • Detecting instances of ambivalence and hesitancy in individuals; and
  • Automatically being able to evaluate clinician reactions in response to patient cues.

It uses advances in machine (ML) and deep learning (DL) models to process multimodal data – including voice and facial expressions – to develop innovative automatic expression recognition (AER) tools

The AER project will generate new annotation schemes to measure individual and clinician expressions, create and score new datasets, and help co-develop ML and DL-based algorithms to be able to automatically detect these expressions. Ultimately, these could be integrated into digital health interventions and assessment tools to improve healthcare practices.

Position summary

 The individual who is selected for this position will be expected to work with study PI’s, Drs. Simon Bacon (Concordia), Eric Granger (ETS), and Kim Lavoie (UQAM), in delivering the project. The MSc student will be able to work on a variety of research-related aspects of the study including:

  • Delivery of the testing protocol
  • Recruitment of participants
  • Post-testing data processing, annotation, and analyses
  • Development of deep learning-based algorithms
  • Participating in knowledge user engagement activities

 Required Qualifications

  • Bachelor’s degree in a related discipline (g., Kinesiology, Computer Science, Psychology, Engineering)
  • Demonstrated research experience (e.g., honours thesis, conference presentations, peer-reviewed publications)
  • Effective oral and written communication skills
  • Excellent interpersonal skills
  • Ability to work independently and collaboratively.

Preference will be given to candidates with

  • Prior experience conducting research in at least one of the following areas
    • Applied psychological assessments
    • Multimodal data capture
    • Deep learning models
  • Ability to communicate (orally) in both English and French
  • Openness to learn new methods and techniques in an applied clinical setting

Provincial, national and international candidates are encouraged to apply

 Start date, Duration, Stipend, and Location

The MSc will start in September 2027 (though there is also the possibility of starting during the summer of 2027).

The funding package consists of a 2-year stipend (consistent with Fonds de Recherche du Quebec funding levels) plus conference / training funding.

The successful candidate will be registered at Concordia University in the Department of Health, Kinesiology, and Applied Physiology or in the Department of Psychology (www.concordia.ca); the actual work would be conducted at the Santé Québec Nord-de-l’Île-de Montréal – Universitaire, Hôpital du Sacré-Coeur de Montréal (https://rechercheciusssnim.ca/). Please note that the language of instruction at Concordia is English.

How to apply

To apply, candidates must complete the online application form and upload the following documents:

  • A complete curriculum vitae, including summary of GPAs and a full publication list (including hyperlinks where possible)
  • A letter of motivation and statement of research accomplishments and future research goals, which should be no longer than 2 pages.
  • At least one written example of a research focused output, e.g., research article, honours thesis, class-based research paper.

Queries about the application should be sent to apply@mbmc-cmcm.ca.

The closing date for receipt of applications is Friday November 27, 2026, 5 pm ET. Interviews will be conducted in December 2026 and January 2027. The successful candidate will need to apply to the University by the official application deadline.