Organization: U.S. Environmental Protection Agency (EPA)
Reference Code: EPA-ORD-CESER-BIL-2024-04
How to Apply: A complete application consists of:
- An application
- Transcript(s) – An unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors may be submitted. All transcripts must be in English or include an official English translation.
- A current resume/CV, including academic history, employment history, relevant experiences, and publication list
- Two educational or professional recommendations.
All documents must be in English or include an official English translation.
Application Deadline: 9/27/2024 3:00:00 PM Eastern Time Zone
Description: A 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) located in Cincinnati, Ohio. If selected for the opportunity, the participant will need to relocate to the appropriate EPA facility. The relocation costs are not reimbursable. The opportunity is not 100% remote, but limited remote participation may be considered at the mentor’s discretion.
Research Project: The research participant will gain educational and professional benefits through involvement in a statistical modeling project focusing on machine learning (ML) approaches appropriate for characterizing the likelihood of lead service line presence in community neighborhoods and homes.
Under the guidance of a mentor, research activities may include:
- Reviewing current state of knowledge on machine learning applications for LSL identification
- Investigating approaches to integrate field generated data into ML analyses
- Exploring novel approaches to ML analyses e.g. ensemble modeling
- Integrating recent EPA data science resources into LSL research
- Application of machine learning methods to community level decision-making for LSL identification
- Developing guidance on applying and interpreting ML LSL results
- Presenting research at professional conferences
- Publishing research results in peer-reviewed journals
- Traveling to professional conferences, research facilities, and field sites
Learning Objectives: The research participant will learn to detect and show patterns in user data, make predictions based on these patterns, and generate manuscripts, presentations, and other outputs related to drinking water research projects including lead service line identification projects through collaboration on informational resources. The participant will learn basic machine learning methods and integrate recent EPA data science resources into LSL research.
Mentor(s): The mentor for this opportunity is Caleb Buahin (Buahin.Caleb@epa.gov).
Anticipated Appointment Start Date: August/September 2024. All start dates are flexible.
Appointment Length: The appointment will initially be for one year and may be renewed three to four additional years upon EPA recommendation and subject to funding availability.
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 stipend range for this opportunity is $71,984 - $86,279 per year plus a travel/training allowance.
EPA Security Clearance: Completion of a successful background investigation by the Office of Personnel Management (OPM) is required.
Qualifications: The qualified candidate should have received a doctoral degree in one of the relevant fields (e.g. Computer Science, Statistics, Environmental Modeling), or be currently pursuing the degree with completion before the appointment start date. Degree must have been received within five years of the appointment start date.
Preferred Skills: Desired background and/or expertise includes data mining, statistics, machine learning, computer programming, artificial intelligence, and mathematics.
Eligibility Requirements:
- Citizenship: LPR or U.S. Citizen
- Degree: Doctoral Degree received within the last 60 months or currently pursuing.
- Academic Level(s): Graduate Students or Postdoctoral.
- Discipline(s):
- Chemistry and Materials Sciences
- Computer, Information, and Data Sciences
- Engineering
- Mathematics and Statistics
Questions: Please see the FAQ section of our website. For additional questions about the application process please email ORISE.EPA.ORD@orau.org and include the reference code for this opportunity.
