A postdoctoral research project training opportunity is currently available at the Institute for the Environment with the University of North Carolina at Chapel Hill. This appointment will be in the Institutes Center for Environmental Modeling and Policy Development (IE-CEMPD). The selected candidate will work with Dr.
Sarav Arunachalam in IE-CEMPD, developing and applying techniques for creating high resolution fields of ambient air quality exposures. Sponsored by the U.S. EPA, the candidate will work on a range of tasks including: a) Investigate the utility of the existing landscape of observational datasets and models to support estimating fine-scale air quality on a real-time basis, including evaluating computational needs, data access and integration, and time-resolution and availability of model inputs, b) Develop methods to integrate real-time data from multiple observational datasets (e.g., stationary sensors, mobile monitoring vehicles, citizen science portable sensors, reference monitors, remote sensing products, live traffic activity and meteorological data) and predictive models to create accurate, fine-scale air quality maps at community/neighborhood scales, c) Develop best practices and guidance for data fusion, interpretation, and communication of results, d) Estimate and compare/contrast exposures to school children during different commute modes, and e) Enhance inhalation dose models using data from Accelerometers, GPS, etc. for multiple pollutants.
Beyond these tasks, the chosen candidate will also have an opportunity to work with other ongoing projects within IE-CEMPD in the field of emissions, air quality and climate modeling, and likely lead the development of new project ideas. The ideal candidate should have a strong background in numerical modeling specifically with local-scale dispersion models such as R-LINE, SCIPUFF and AERMOD or other, and quantitative analysis of models and observational data using Python, Matlab, R, GIS, etc. Additional desired qualifications are a) strong communication skills written and oral, b) computer skills related to working with complex models and large datasets, c) software skills needed to work with multiple observation datasets in situ and remotely sensed (such as NASAs satellite data products) for model evaluation and source attribution, d) a strong desire/motivation to develop scientific analyses of environmental problems for decision-making in support of national and international policies, and e) ability to work in a team environment. Web programming skills are a plus.Ph.D. in Atmospheric or Environmental Sciences and Engineering or similar
The University Of North Carolina