Is your R script taking too long? Do you find yourself rerunning things over and over? Are you using loops or lapply and think that these are slowing you down? In many cases, working with parallel computing in R can help solves these problems. Working on a super computer with 100s or 1000s of nodes can potentially help a lot.
As part of a multidisciplinary study of vegetation, fire and permafrost dynamics, the successful applicant will develop spatial simulation models to forecast the abundance and spatial distribution of caribou habitat in relation to climate change, fire and human landuse in the Northwest Territories. The models are to be implemented in SpaDES, a new R package for spatial simulation and individual based modelling. Part of the thesis will involve integration of the team’s research findings, scenario development and the implementation of simulation experiments. However, the student will also be expected to conduct applied research in one related topic (e,g, vegetation dynamics, caribou movement) according to their interest, the results of which would be included as a model component. The qualifications are strong quantitative skills and an interest in spatial simulation independent of disciplinary background. A high level of written communication skills in English is essential. Programming experience (e.g. in R, Python) would be an asset, but modelling courses are available in the lab.