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Wildland Fire Environmetrics Research Scientist - NRCan
Position Summary :
Natural Resources Canada (NRCan) is looking for a postdoctoral researcher to develop and apply statistical methods to predict the occurrence of severe wildfires in Canada. The researcher will work with fire scientists from NRCan and statisticians at the University of Guelph as part of an interdisciplinary “Daily Fire Occurrence and Burn Probability” project.
We seek a statistician or a quantitative environmental scientist with expertise and interest in statistical methods relevant for environmental / atmospheric sciences. The position offers an excellent environment for working with a highly skilled interdisciplinary team in NRCan and at Guelph University. The expertise of team members includes applied statistical modelling, stochastic processes, machine learning, climate analyses, and wildfire behavior and occurrence prediction. The successful candidate will focus on the analysis of the influence of weather and other environmental variables on the occurrence of lightning, human-caused and severe fires, and the development of predictive models for such occurrence. Understanding and predicting severe fires is an area of intensive current research in the fire science community and critically important to public safety.
The position requires developing and applying a combination of statistical methods such as spatio-temporal statistics and machine learning, to estimate the probabilities of fire events under different atmospheric and environmental conditions. A key focus will be to quantify the uncertainty in the probabilities in light of a wide variety of sources of uncertainty. The researcher will evaluate, extend and implement existing methods and develop new statistical frameworks and methods to predict the occurrence of wildfires in relation to forecasted weather and other explanatory variables. The researcher will work with fire scientists to apply and implement these methods within a wildfire information system.
Specific Responsibilities :
- Develop and apply statistical methods for prediction of the occurrence of severe wildfires.
- Compare predictions to past observations to evaluate the fidelity of models and examine the risk of model failure (false negatives).
- Produce and deliver oral and written presentations of scientific results.
- Work effectively in an integrated team.
Essential Qualifications :
Additional Desired Qualifications :
How To Apply :
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