Texas A&M University
College Station, TX
Postdoctoral research associate at Texas A&M University in Risk Assessment and Computational Toxicology for Environmental Disasters
What kind of chemical contamination has occurred after Hurricanes Harvey and Irma? What are the risks? How do we decide if it is safe to move back or rebuild? Help us answer these questions by joining the Texas A&M Superfund Research Center as a Postdoctoral Research Associate in the Risk Assessment and Computational Toxicology Laboratory of Dr. Weihsueh Chiu*. This position is open immediately and will be filled as soon as a suitable applicant is available.
The newly established Texas A&M University Superfund Research Center (https://superfund.tamu.edu/) investigates the impacts of environmental emergency-related contamination events, such as those that occurred after Hurricanes Harvey and Irma. In particular, Center project teams will work to measure “known-unknown” or “unknown-unknown” contaminants in and around the Houston/Galveston Bay area, expanding the current understanding of environmental exposures. Moreover, it will go beyond the “one-chemical-at-a-time” approach by focusing on “whole mixtures,” developing approaches that can be applied more generally following natural or man-made environmental disasters.
This position is in the Center’s Decision Science Core, led by Dr. Chiu, which supports the Center’s research projects by synthesizing relevant scientific data and conclusions for use by those involved in risk management decisions.
Key duties of this position will include:
• To apply and advance methods for toxicokinetic modeling -based dosimetry calculations for large numbers of individual chemicals, defined mixtures, and environmental mixtures. These include high-throughput and probabilistic computational approaches to model both individuals and population variability. These models will be used for both “forward” dosimetry for prediction as well as “reverse” dosimetry for in vitro-to-in vivo extrapolation, supporting multiple Center Project teams.
• To apply and advance methods for human health risk modeling to predict hazards and risks for individual chemicals, defined mixtures, and environmental mixtures. These include use of computational and probabilistic dose-response methods to improve upon existing toxicity values, working with the Center’s Exposure Science Core to convert between environmental concentrations and population exposures, working with the Center’s Data Science Core to develop computational read-across approaches, and supporting economic impact modeling conducted by collaborators at the University of North Carolina.
In all cases, creative thinking and innovation will be needed to move beyond traditional “one-chemical-at-a-time” approaches to addressing whole mixtures in a rapid and efficient manner appropriate for application to environmental disasters. This position offers excellent exposure to inter-/trans-disciplinary team science, integrating data and expertise across the source-to-outcome continuum to address the critical emerging risk of catastrophic chemical contamination events caused by natural and man-made disasters.
Successful candidates should have a doctoral degree (PhD or equivalent) in a relevant field, including but not limited to: Biology, Engineering, Environmental Science, Epidemiology, Genetics, Public Health, Statistics, and Toxicology. Because of the nature of this laboratory, demonstrated skills in quantitative and computational methods and statistics are also required . Previous experience with toxicokinetic modeling and quantitative risk assessment are highly recommended. The initial appointment will be for one year with the intention of extending the appointment if mutually agreeable. Salary is commensurate with NIH guidelines. A full package of benefits is included in accordance with Texas A&M policies.
The Texas A&M System is an Equal Opportunity/Affirmative Action/Veterans/Disability Employer committed to diversity. Candidates from historically under-represented minority groups, with socioeconomic or other educational disadvantages, who are first-generation college graduates, who are veterans, or who have with disabilities are especially encouraged to apply.
To be considered, please submit a brief personal statement including previous research experience and a curriculum vitae including contact information for three references.