MSc: Enhancing digital health behaviour change programs using deep learning models of emotional expression

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). In traditional face-to-face healthcare, clinicians detect these states through speech patterns and non-verbal cues. However, in digital health (eHealth) interventions, where physical interactions are limited, assessing ambivalence and hesitancy remains a significant challenge. Advances in machine learning (ML) and deep learning (DL) now allow for the processing of multimodal data—including voice and facial expressions—opening the door to developing innovative tools based on automatic expression recognition (AER).

The AER project will generate new annotated data and algorithms for the expression of ambivalence and hesitancy. Ultimately, these could be integrated into digital health interventions to identify people’s ambivalence and hesitancy towards their goals.

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:

  • A Bachelor’s degree in a related discipline (g., Kinesiology, Computer Science, Psychology, Engineering)
  • Effective oral and written communication skills
  • Excellent interpersonal skills
  • Demonstrated research experience (e.g., honours thesis, conference presentations, peer-reviewed publications)
  • Ability to work autonomously and take a lead role on projects under the supervision of the principal investigators

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 2026 (though there is also the possibility of starting during the summer of 2026); funding has already been received.

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 (www.concordia.ca); the actual work would be conducted at the CIUSSS-NIM, Hôpital du Sacré-Coeur de Montreal (https://rechercheciusssnim.ca/). Please note that the language of instruction at Concordia is English.

To apply, please forward the following:

  • A complete curriculum vitae, including summary of GPA’s, a full publication list (including hyperlinks where possible) and email contact details for two referees
  • A letter of motivation and statement of research accomplishments and future research goals, which should be no longer than 2 pages.
  • An example of written research work

How to apply:

  • The complete application package must be emailed to: apply@mbmc-cmcm.ca. Please include “MSc AER” in the subject line.
  • Queries about the application should be sent to Dr. Bacon (simon.bacon@concordia.ca).
  • The closing date for receipt of applications is Friday November 28, 2025, 5 pm ET. Interviews will be conducted in December 2025 and January 2026. The successful candidate will need to apply to the University by the official application deadline.