EPA Modeling Chemical Process Environmental Releases and Exposures Fellowship

Organization
U.S. Environmental Protection Agency (EPA)
Reference Code
EPA-ORD-CESER-LRTD-2023-02
How to Apply

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A complete application consists of:
  • An application
  • Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted. All transcripts must be in English or include an official English translation. Click here for detailed information about acceptable transcripts.
  • A current resume/CV, including academic history, employment history, relevant experiences, and publication list
  • Two educational or professional recommendations. Click here for detailed information about recommendations.

All documents must be in English or include an official English translation.

Application Deadline
8/18/2023 4:02:12 PM Eastern Time Zone
Description

*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 LocationA research opportunity is currently available at the Environmental Protection Agency (EPA), Office of Research and Development (ORD), Center for Environmental Solutions and Emergency Response (CESER), Land Remediation and Technology Division (LRTD) located in Cincinnati, Ohio.

Research Project: This is a research training opportunity provided by the Environmental Decision Analytics Branch (EDAB) in the Office of Research and Development. EDAB conducts research in fields related to life cycle assessment, decision making, and system modeling. A current program in EDAB is Rapid Exposure and Dosimetry, related specifically to the rapid estimation of releases and exposures. This effort has many facets, one of which is to develop methods to rapidly estimate chemical releases for exposure and risk assessment applications, including manufacturing, processing, and use of a chemical through models known as Generic Scenarios. A Generic Scenario is an EPA Office of Pollution Prevention and Toxics term for an equation-based model that describes the release of a chemical during a well-defined industrial activity or set of activities. These activities, in such systems as manufacturing, processing, and use of chemicals, are described by process flow diagrams, process models, stream tables, etc. with mass and energy balance and transfer equations. The rapid estimation of chemical releases expands the system of interest beyond the equipment to worker exposure and ambient environments. The project answers questions about the amount and concentration of a chemical predicted to be in environmental exposure pathways such as water releases, indoor air, on surfaces, etc. Modeling can include engineering approximations to equipment operation and release processes, estimating model inputs, and determining relationships between inputs and result uncertainty. Methods of collecting data from EPA databases and through automated data scraping will be developed based on model needs. Computer-based statistical methods will be applied as fit for purpose, including machine learning techniques for clustering, classification, and regression. Development of a database and its use in predicting releases will be used as appropriate to extrapolate beyond the specific chemicals and circumstances studied in equation-based modeling. The research participant will collaborate with scientific staff in ORD in training opportunities related specifically to the rapid estimation of releases and exposures.

Under the guidance of a mentor, research activities may include:

  • Manufacturing process modeling, chemical use modeling, mass transfer modeling,
  • Model input estimation, uncertainty analysis, data source identification and data collection,
  • Statistics, computer programming, artificial intelligence, machine learning, knowledge discovery and data mining,
  • Prediction of chemical releases and concentrations for exposure and risk assessment purposes,
  • Contributing to the preparation of peer-reviewed journal articles and disseminating research results to project partners, stakeholders, and the research community, and
  • Presenting research at regional, national, and/or international conferences and workshops.

Learning ObjectivesThe research participant will be afforded the opportunity to interact with internationally recognized leaders, both within and outside the EPA, in chemistry, engineering, and the environment. The research participant will have the opportunity to publish original research. It is expected that this research training opportunity will provide an early career scientist with knowledge, skills, and abilities needed to apply new technologies and associated data to applied engineering, industrial hygiene / exposure, and environmental decision-making contexts and to pursue a professional career in engineering / applied sciences research.

Mentor(s)The mentor for this opportunity is Raymond Smith (smith.raymond@epa.gov). If you have questions about the nature of the research please contact the mentor(s).

Anticipated Appointment Start Date: September 5, 2023.  All start dates are flexible and vary depending on numerous factors. Click here for detailed information about start dates.

Appointment LengthThe appointment will initially be for one year and may be renewed up to three or four additional years upon EPA recommendation and subject to availability of funding.

Level of ParticipationThe appointment is full-time.

Participant StipendThe participant will receive a monthly stipend commensurate with educational level and experience. Click here for detailed information about full-time stipends.

EPA Security ClearanceCompletion of a successful background investigation by the Office of Personnel Management (OPM) is required for an applicant to be on-boarded at EPA.

ORISE InformationThis 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.

ORISE offers all ORISE EPA graduate students and Postdocs a free 5 year membership to the National Postdoctoral Association (NPA).

The successful applicant(s) will be required to comply with Environmental, Safety and Health (ES&H) requirements of the hosting facility, including but not limited to, COVID-19 requirements (e.g. facial covering, physical distancing, testing, vaccination).

Questions: Please see the FAQ section of our website. After reading, if you have additional questions about the application process please email ORISE.EPA.ORD@orau.org and include the reference code for this opportunity.

Qualifications

The qualified candidate should be currently pursuing or have received a doctoral degree in one of the relevant fields (e.g. Chemical Engineering, Civil Engineering, Environmental Engineering, Environmental Science, Industrial/Occupational Hygiene). Degree must have been received within the past five years.

Preferred skills:

  • Desired background and/or expertise includes process and fate & transport modeling, chemical industrial/occupational hygiene, data mining, statistics, machine learning, computer programming, and mathematics.
  • Knowledge of factor analysis / least-squares statistics, methods such as base-case ratios / dimensionless quantities, and a desire to work on environmental problems
Eligibility Requirements
  • Citizenship: U.S. Citizen Only
  • Degree: Doctoral Degree received within the last 60 months or currently pursuing.
  • Discipline(s):
    • Chemistry and Materials Sciences (1 )
    • Computer, Information, and Data Sciences (3 )
    • Engineering (8 )
    • Environmental and Marine Sciences (2 )
    • Life Health and Medical Sciences (4 )
    • Mathematics and Statistics (11 )
    • Physics (1 )