Research program title
Development of a Detection System for Problematic Online Gambling
With the rapid development of digital technologies, gambling has been popularized online, raising new challenges for the prevention of gambling problems. This postdoctoral training opportunity involves working on the first study developing a system of indicators for the detection of risky patterns of online gambling. By combining live activity behavioural data with information on the severity of gambling problems, this project will develop algorithms to identify 1) at-risk gamblers requiring more intensive preventive messages, and 2) problem gamblers to propose referrals to specialized treatment services. Ultimately, this project will develop recommendations to support the implementation of dynamic preventive tools on online gambling sites for the screening and intervention of high-risk and problem gamblers.
The successful candidate will:
- Demonstrate a knowledge and understanding of programming languages, machine learning methods and supervised
- Submit two scientific articles to peer-reviewed journals in collaboration with the research supervisors.
- Disseminate the findings of the study through knowledge translation activities, i.e the creation of a report
- Interact with our academic and policy-oriented partners and collaborators
- have experience with machine learning packages in R
- have a knowledge of the field of gambling and addictions
The training plan is designed around activities that will enhance and foster four types of competencies: 1) Knowledge and expertise in online gambling; 2) Proficiency in state-of-the-art statistical techniques; 3) skills in knowledge translation and exchange (KTE) within academia and among various non-academic stakeholders; 4) Developing and sustaining collaborations and networks
Academic qualifications required
PhD in any social science discipline (Sociology, Psychology, Demography) or epidemiology with advanced expertise in quantitative data analysis. The candidate is expected to have five years of experience in research. Fluency in French is an asset.