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Thank you for your interest in joining the lab!

Here’s some information to give you a sense of whether the lab would be a good fit and what I’m looking for in a prospective trainee.

After reading below, please email me ([email protected]) with a description of how you think you could fit with the lab, what position you would be interested in (undergraduate, graduate, postdoc), and your curriculum vitae. In your email, please indicate what semester you are considering (e.g., Fall 2025) and indicate days/times you would be available for a virtual meeting. It's also a good idea to have an email subject that is informative (e.g., Prospective Master's student Fall 2025). It's a good idea to read through information about graduate studies in the Department of Psychology at Concordia. It is highly likely you will know more about the admissions process than I will at this point.

About the lab:
Everyone deserves access to opportunities that will allow them to lead healthier, happier, longer lives. We will focus on the design of better health-enhancing interventions and policies to achieve health for all. Our work is at the intersection of digital health and health neuroscience, combining frameworks across affective, cognitive, and developmental sciences to best answer our research questions.

We are developing methods and conducting studies that allow us to intervene early, understand whole-person health (mind and body), support wellbeing in everyday life using technology, and examine the complex interplay among factors influencing wellbeing.

Guiding research aims:

• To intervene early (e.g., family and school settings) for positively influencing health trajectories for all
• To integrate mind and body and to understand personal contextual factors (family, neighbourhood, school, culture, etc.) to achieve health and wellbeing for all
• To design ecologically-valid interventions that people can draw upon at any moment in their everyday life 
• To increase population health efforts that include personalization in communicating and delivering behaviour change via digital and wearable technologies
• To design interventions and policies with the most promise of reducing health inequities, we aim to use methods that allow us to model the complex interplay among factors influencing health by considering whole-person (mind-body) approaches that situate individuals within their complex environments (e.g., family, peers, neighbourhoods, schools, etc.)
• To increase person-specific wellness initiatives as one size does not fit all

Here is an image that depicts some of our research areas:

Prospective trainees should be interested in one or more of the following areas:

To better understand how lifestyle behaviours influence brain health during development:

• We are interested in how lifestyle behaviours (e.g., physical activity, alcohol use) influence how we handle our emotions, how we think, and our relationships with others from early childhood through adolescence into adulthood.

To better understand the mechanisms underlying the links between body and brain health:

• We are interested in how our brains and bodies interact and so we collect multimodal data to be able to understand and predict wellbeing. For example, in studying the pathways through which physical activity supports emotion regulation, we collect brain data (e.g., MRI, EEG) as well as clinical measures (e.g., self-reported emotions, depressive symptoms), and ambulatory data (e.g., wearables, smartphones)

To study the relationships among body, brain, and pressing societal issues:

• We are interested in embedding our research within digital and wearable health technologies to better understand how physical and mental wellbeing interact with race, ethnicity, education, socioeconomic status, and other characteristics that make people who they are. 

To advance digital tools and wearable technologies or supporting health and wellbeing in everyday life:

• We are interested in making health-enhancing programs more accessible to all so that everyone has the opportunity to lead healthier, happier lives. This involves using tools that let us measure wellbeing outside the lab and thinking about mobile health solutions that get interventions into the palm of people's hands and in their daily lives (e.g., school).

Prospective trainees should be interested in developing some of the following skills:
1. Advanced quantitative skills (e.g., multilevel modeling, network science, natural language processing, machine learning, and structural equation modeling).
2. Programming skills (e.g., R, Python, MATLAB).
3. Open science and reproducible research practices.
4. Use a variety of methods in the lab and ecologically-valid naturalistic measures (e.g., EEG, MRI, cardiorespiratory testing, eye-tracking, mobileEEG, actigraphy, smartphone experience-sampling and daily diaries, digital health and wearable technologies).
5. Think deeply about societal issues, methods, policies, and how our research can be mobilized to address real-world problems.
6. Reasoning and writing skills for communication with scientific and non-scientific audiences.

What are you looking for in prospective trainees?
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Criterion	Example
Has research interests in digital health, wearable technologies, health neuroscience, and wellbeing.	You can provide a compelling statement of purpose of how you became interested in these areas and provide examples of research questions you might be interested in pursuing.
Is resourceful, perseverant, and growth-minded in the face of challenges	Provide examples of overcoming obstacles, finding alternative solutions, sticking with it when it gets tough (e.g., when learning something new and difficult or on a challenging project or in your personal life).
Is interested in learning and developing advanced quantitative skills	Taking and doing well in statistics, math, engineering, or computer science classes is a good indicator. But, direct experience in an environment where you have experience doing statistics or thinking and communicating quantitative information are also ways you can show this.
Has strong reasoning and writing skills	Strong writing samples of your own work (i.e., not written in large part by an advisor). A publication or honours thesis is helpful; other examples could include a lab report, literature review, or class paper or some type of communication from your job.
Values collegiality, collaborative work, and a team mentality.	Specific examples of how you have supported and helped others in your previous work experience or in teams.
Values critical curiosity, personal development, and self-directed learning.	How have you had to learn something on your own (e.g., programming or other languages) and how have you shown that you are committed to always learning and not just accepting but questioning the things you learn? A big part of what we do in research is being able to direct your learning and interests to develop skills yourself; how have you done this before in your work or life?
Multilingualism	Montréal and Québec are predominantly French speaking. Making our research accessible in Canada also requires being able to communicate with participants and stakeholders in English and French. Other languages are assets as we live in an ever-changing multilingual world and forging international collaborations will be easier with multiple languages.
Coding and programming	R, Python, and MATLAB are the dominant languages we use to do our daily activities. Showing how you use these and are still developing these skills (learning never ends). Research is showing that coding is like learning a foreign language, so you can also demonstrate how you will apply your experience learning a language to learning these skills.