EPA Water Quality Modeling and Economics Fellowship – Washington DC

U.S. Environmental Protection Agency (EPA)
Washington, DC
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Last Date to Apply
*Applications may be reviewed on a rolling-basis and this posting could close before the deadline. Click here for information about the selection process. EPA Office/Lab and Location: One research opportunity in water policy and regulation is available at the Environmental Protection Agency (EPA), Office of Water (OW), in the Immediate Office (IO) of the Assistant Administrator for Water located in Washington, DC. Research Project: The goal of this research project is to conduct research on water quality modeling and water quality valuation. This research may support the development of tools such as the Hydrologic and Water Quality System (HAWQS), a nationwide Soil and Water Assessment Tool (SWAT) based water quality modeling system, and the Benefits Spatial Platform for Aggregating Socioeconomics and H2O Quality (BenSPLASH), a nationwide water quality valuation model. With guidance from the mentor, the research participant may be involved in in the following training and team activities: - Collect and analyze water quality data for model calibration and validation using statistical programs, GIS tools, and databases - Conduct research to explore impacts and outcomes of policy choices and communicate results, including quantifying and valuing changes in water quality - Collaborate on developing methodologies to incorporate and apply new or existing modeling and valuation approaches and data to HAWQS and BenSPLASH on a national scale Learning Objectives: - Learn and develop expertise on HAWQS (https://epahawqs.tamu.edu/) and SWAT (https://swat.tamu.edu/software/) hydrologic and water quality models through online documentation, training, and weekly HAWQS development meetings and discussions - Learn and develop expertise on BenSPLASH (Benefits Spatial Platform for Aggregating Socioeconomics and H2O Quality) through BenSPLASH development meetings and discussions Mentor(s): The mentor for this opportunity is Joel Corona (corona.joel@epa.gov). If you have questions about the nature of the research please contact the mentor(s). Anticipated Appointment Start Date: Fall 2020. All start dates are flexible and vary depending on numerous factors. Click here for detailed information about start dates. Appointment Length: The appointment will initially be for one year and may be renewed up to three additional years upon EPA recommendation and subject to availability of funding. Level of Participation: The appointment is full-time. Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience. The current annual stipend rate for Master's degree is $59,534 per year and doctoral degree is $72,030 per year. Click here for detailed information about full-time stipends. EPA Security Clearance: Completion of a successful background investigation by the Office of Personnel Management (OPM) is required for an applicant to be on-boarded at EPA. ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and EPA. Participants do not become employees of EPA, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE. Questions: Please see the FAQ section of our website. After reading, if you have additional questions about the application process please email EPArpp@orau.org and include the reference code for this opportunity.
The qualified candidate should have received or be currently pursuing a master's or doctoral degree in one of the relevant fields. Degree must have been received within five years of the appointment start date. Preferred skills: - Skills or educational background in environmental modeling and/or environmental economics, preferably with interest/background in water-related issues - Familiarity with one or more popular programming languages such as R, Python, and SQL
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