Vacancy ID: PDS004450 Position Summary/Description: This position may be eligible for a hybrid work arrangement that may include a partially remote work location, consistent with System Office policy. UNC Chapel Hill employees are generally required to reside within a reasonable commuting distance of their assigned duty station. Postdoctoral research project training opportunities are currently available at the Institute for the Environment with the University of North Carolina at Chapel Hill. These appointments will be in the Institute’s Center for Environmental Modeling and Policy Development (IE- CEMPD ). The selected candidate will work with Dr. Sarav Arunachalam in IE- CEMPD , to a) develop exposure-based categories of novel and emerging pollutants of interest such as Per- and polyfluoroalkyl substances ( PFAS ) using statistical approaches based on sources and occurrence patterns in air, water, dust, and other environmental and biological media, and b) advance understanding of human exposure to PFAS by providing the data needed to: identify, characterize, and predict important human exposure sources and pathways, evaluate the contribution of these exposure sources/pathways to PFAS body burdens, and prioritize efficient and effective collection of PFAS exposure information and anticipate exposures to new PFAS . The candidate will work on a range of tasks including: a) Perform literature review to assess current state-of-the-art in developing exposure estimates for emerging pollutants like PFAS , b) Perform data analyses and modeling to develop exposure-based PFAS categories and contribute to insights on PFAS exposure sources and pathways using novel approaches like machine learning using multiple observational datasets, c) Collaborate with other stakeholders including data scientists, and d) Develop peer reviewed publications and project reports.. Beyond these tasks, the chosen candidates will also have an opportunity to work with other ongoing projects within IE- CEMPD in the field of emissions, air quality and climate modeling, to be mentored by the PI to lead the development of new project ideas and develop grant proposals, and provide support to junior staff / graduate students on related tasks. Extension beyond year 1 subject to funding availability and performance reviews. Education and Experience: Desired qualifications are a) chemistry and chemical mechanisms, b) proficiency in machine learning and other statistical methods, c) strong communication skills – written and oral, d) software skills needed to work with multiple observed and model datasets, e) a strong desire/motivation to develop scientific analyses of environmental problems for decision-making in support of national and international policies, and f) ability to work in a large multi-disciplinary team environment. At least 1 – 3 years of post-graduate experience will be considered a plus.