Seeking Graduate Students for Fully Funded Research on Agricultural Systems

March 25, 2016

We are seeking two PhD students (and may consider highly skilled students interested in obtaining a Master’s) with deep interests in agricultural systems, ecology, geography, or computer science to join our research team. Applicants do not need to have expertise or backgrounds in each of the above disciplines as unique expertise and depth in each of these disciplines is required to make novel scientific, empirical, and modelling advances and contribute to the success of the larger project. We are seeking specific knowledge and skills in ecological fieldwork (soil science and flora species identification), modelling (using GPGPUs, agent-based modelling, ecosystem models), spatial analysis (GIS and spatial statistics), and experience conducting social surveys. However, we are in search of the best applicant and fit with our research team so a keen individual seeking experience in these areas may be successful. Successful applicants will have additional opportunities to work on other research projects in wetland reclamation, modelling land-use and land cover change, and other projects within the Modelling and Spatial Analysis Lab as well as work with others beyond the lab in the Faculty of Environment and beyond.

Applicants are asked to submit the following details

  • Cover letter outlining your fit for the position.
  • CV/resume
  • Unofficial grade transcripts
  • Writing sample (paper submitted for publication or thesis)

The positions will remain open until filled and their start date is flexible. Please submit application contents via email to: dtrobins@uwaterloo.ca

Project Summary

The proposed research estimates the impacts of changes in climate, technology, and policy on farm livelihood, crop production, and ecosystem function across southern Ontario. Using the innovative combination of unmanned aerial vehicle equipment, survey, and ecological fieldwork, new kinds of data are collected and analyzed to improve our understanding of how agricultural decisions are made and can change over time and across space. By synthesizing these data in a model, the proposed research leverages simulated scenarios to evaluate potential farm responses and, in collaboration with farmers, identify land management strategies that can close the gap between potential and actual yields.

The research team working on this project will comprise two undergraduates, two Masters, and two PhDs.  All graduate students on the project will receive UAV training from the Waterloo-Wellington Flight Centre and gain experience using UAV systems. In addition to planning and executing fieldwork, students will acquire knowledge and skills in programming, geographical information systems, remote sensing software, social and ecological fieldwork, statistics, and simulation modelling. The combination of these skills is unique and are rarely available within a single research project.

Funding

Full funding is available for PhD and Masters students, Canadian or International. The successful applicant would be funded through a combination of teaching assistant positions in the Department of Geography and Environmental Management at the University of Waterloo and research assistant positions funded by an external research award.

Applicants must meet the minimum requirements for admission to the Department of Geography and Environmental Management at the University of Waterloo.

Additional Research Opportunities

Successful applicants will join a growing graduate student and post-doctoral research team under the guidance of Dr. Robinson and part of the Geospatial Innovation Centre co-managed with Dr. Pete Deadman, and Dr. Peter Johnson in the Faculty of Environment at the University of Waterloo. Access to servers and a wide range of software (e.g., ESRI and ArcServer, Alteryx, Oracle Spatial, eCogition, Pix4D, among others) and new Unmanned Aerial Vehicle and Socio-Ecological infrastructure acquired from funding provided by the Canadian Foundation for Innovation will provide additional state-of-the-art learning opportunities to develop additional skills to complement those under the presented project.