Mitacs GlobaLink Research Internship Opportunities

I’m happy to announce that I have been approved to offer three research projects for up to six international undergraduate students through the Mitacs Globalink Research Internship program. Undergraduate students from Australia, Brazil, China, France, India, Germany, Mexico, Saudi Arabia, Tunisia, or Ukraine are eligible to apply.

The three programs – which span software development, ecological risk assessment, and human-computer interaction – are outlined below. Each project can support up to two interns.

Student applications are due by September 19th, 2018 at 1:00 pm (PT). If you are interested in applying, click here. For more information about the program, click here.

  • Developing Software for Environment & Health Monitoring

    Students will be tasked to assist in the development of an Android application (as well as a web application) for health and environmental monitoring in the Circumpolar North, and given constraints associated with the digital divide. Specifically, students will work with an interdisciplinary team of undergraduate and graduate students, faculty, government officials, and Inuit researchers to implement mobile and web app functionality that supports the needs of the community of Rigolet, Nunatsiavut, Labrador. This may include using gaming elements to improve engagement with the app, implementing a badging system for skills training, or expanding the instant messaging platform.

  • Sustainable Management of Animal Species Using Simulations and Agent-Based Models

    The student will be assisting a team of undergraduate and graduate researchers to design, implement, and test an agent-based model to investigate the impacts of anthropogenic activities on various different populations of wild animals (likely rare or endangered) to develop a set of potential management actions.

    The specific goals of this project include 1) extend an existing agent-based model to address new species or new anthropogenic risks, 2) identify management scenarios, and 3) evaluate scenarios given different population structures (e.g. populations in decline). The student will also explore cumulative effects dynamics associated with multiple anthropogenic stressors.

    The student will spend the first portion of their internship learning about existing models, team coding practices, and some of the biologically relevant details. The student is not expected to have experience in a specific programming language but should be expected to know how to code, and should have the ability to learn a new programming language.

    Since this is a team project, the intern will be expected to take part in weekly meetings, provide updates about their portion of the project to the team, and actively participate in team decision making. Finally, while the intern will be expected to work independently, they are also expected to communicate any challenges and potential solutions with the team.

  • Investigating Alternative Methods for Data Collection: Gamification, Participatory Design, and Engagement

    Standard phone survey methods are expensive, time-consuming, and difficult to conduct. Ensuring representativity across a broad population (such as the population of Canada, or that within each of the Canadian provinces and territories) is challenging. These challenges are exacerbated by the changing telephone use, from land-line to wireless or listed to unlisted land-line, within various demographic groups. Further, there has been a decline in the number of citizens willing to participate in surveys for epidemiological purposes. This research project will 1) identify a set of alternative data collection methods, including but not limited to, online surveys, mobile applications, social media applications, social media data pulls, participatory design methods, and online games, 2) investigate the utility of each of the alternative methods identified in (1) by using appropriate statistical methods to compare the distribution of age and gender (for example) group specific responses against that observed from traditional survey methods, 3) compare each of the methods identified in (1) to determine the most appropriate method to use for each identified age and gender group (for example), and 4) investigate the use of immediate user feedback and its effects on survey response and spread through social media channels.

 

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