Research Opportunities
Available Research Opportunities
More research opportunities exist than those listed below. If none of the projects listed here are right for you, please browse the faculty members belonging to the departments listed here to find someone who is doing research in a field that interests you.
MSc in Applied Science project in PLANT ECOLOGY (Forest edges)
Supervisor: Dr. Karen Harper
Project Description: I am looking for an accomplished and motivated M.Sc. student to study the impact of harvest roads on nearby vegetation structure and wildlife habitat in Acadian forest in Nova Scotia. The fully-funded two-year project would begin in 2025 in the Masters in Applied Science program at Saint Mary’s University, Halifax, N.S.
Connectivity for wildlife depends on habitat or vegetation structure, which can be impacted by edge influence from roads. The recent transition from clearcutting to an Ecological Forestry model in Nova Scotia requires more frequent harvesting interventions, which may increase the footprint of the road network. Vegetation next to road edges might be affected differently due to increased use. This investigation of the change in vegetation structure from road edges into the forest could include field data collection and drone imagery with LiDAR. Vegetation structure at edges will be compared among different forest types, road widths, road usage and/or edge ages. This joint project between Saint Mary’s University and Dalhousie University is part of the . Students will have opportunities to participate in conferences, training, and networking. Saint Mary’s University is committed to an environment that is inclusive, equitable and dedicated to embracing global perspectives. All enquiries are welcome. This project can be made more accessible by omitting field data collection.
For more information email: Karen.Harper@smu.ca
Forest Edge Research Network (FERN),
MSc and PhD Research Opportunity: Explainable Three-Way Data Analytics
Supervisors: Dr. Mengjun Hu (¶¶ÒõÊÓƵ)
Project Description: I’m looking for students to pursue their thesis research on explainable approached to data analytics using three-way decision theory. Three-way decision applies a philosophy of thinking in threes, a methodology of working with threes, and a mechanism of processing through threes. It has been proven to be an efficient and effective tool in many data analytics topics, particularly demonstrating its superiority in explainability. Students may work on either theoretical or practical aspects in a few specific directions, such as three-way classification, three-way clustering, three-way conflict analysis, and three-way concept analysis.
Stipend: tbd
Start Date: tbd
For more information, email: mengjun.hu@smu.ca