Hawaii Fire Portal

The Department of Applied Ecology at North Carolina State University, in collaboration with the Department of Statistics, the North Carolina Cooperative Fish and Wildlife Research Unit, and the USGS Southeast Climate Adaptation Science Center, will be hiring a Postdoctoral Research Scholar in data science to assist with efforts to develop a prototype early warning system for Prescribed Fire Managers (PFMs). The primary research objective of the successful candidate is to characterize short, medium, and long-term climatological-risk for PFMs in the Southeast US, and to build a framework that allows for optimal decision making under uncertainty.

The successful candidate will work with Drs. Brian Reich (Statistics), Jaime Collazo (Applied Ecology), and Adam Terando (USGS) to model environmental conditions conducive to prescribed burning activities over time scales of days to decades in the future. Three major objectives of the position include 1). Define, identify, and model ‘fail-states’, or the sets of conditions that PFMs wish to avoid 2) Model risk exposure of PFMs given existing numerical model simulations of future climate over near-term (days) to long-term (decades) time scales, and 3) develop spatio-temporal models to characterize extreme wildfire risk on decadal time scales.

The incumbent will also join a national cohort as part of the National and Regional Climate Adaptation Postdoctoral Fellows (CAPF) Program. The SE CAPF scholar will collaborate with other cohort scholars from across the country on national-scale research and synthesis on climate-fire issues and participate in regular training and professional development opportunities, including training on translational ecology, co-production of actionable science with natural resource decision-makers, and interdisciplinary collaboration.

This is a two (2) year position, contingent on availability of funding, based in the Department of Applied Ecology and the Southeast Climate Adaptation Science Center at North Carolina State University in close collaboration with the Department of Statistics. The successful candidate will be jointly mentored by Drs. Brian Reich, Adam Terando, and Jaime Collazo.