EPA Bioinformaticist/Data Scientist Fellowship

Organization
U.S. Environmental Protection Agency (EPA)
Reference Code
EPA-ORD-CCTE-BCTD-2021-02
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
9/16/2021 3:00:00 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 available at the Environmental Protection Agency (EPA), Office of Research and Development (ORD), Center for Computational Toxicology and Exposure (CCTE), Biomolecular & Computational Toxicology Division (BCTD) located in Research Triangle Park, North Carolina.

CCTE is responsible for developing new computational tools and providing quantitative analysis for improving environmental risk assessments and regulatory decisions pertaining to chemical safety and sustainability.

Research Project: This research project aims to develop computational methods to predict the safety of chemicals using high-throughput transcriptomics and imaging-based phenotypic profiling data  across multiple cell lines and animal models. The tools to be used include novel transcriptomic data generated within EPA, publicly available databases of transcriptomic signatures and pathways, and outputs of various predictive models of chemical action. The project integrates bioinformatics, data science, software engineering, applied statistics, and predictive mathematical modeling.

The research participant may develop novel bioinformatics and biostatistics applications to analyze transcriptomics and high-content imaging data streams relevant to toxicological testing. Research activities may include:
  • developing a data science infrastructure to identify chemical-responsive genes and pathways
  • curating and managing large-scale heterogeneous chemical safety screening data
  • evaluating latent variable methods to infer the predominant signals of interest in high-dimensional data with complex correlation structures
  • applying machine-learning methods to infer molecular impacts of chemical exposure

The research participant may author or co-author on peer-reviewed publications, and will present at local and national meetings. The participant will be a member of a multi-disciplinary research team.

Learning Objectives: This is a research training appointment wherein the participant will gain education and training in the general areas of bioinformatics, data science, transcriptomics, computational toxicology, and mathematical modeling in preparation for future career opportunities across government, industry, and academic sectors.

Mentor(s): The mentor for this opportunity is Logan Everett (everett.logan@epa.gov). If you have questions about the nature of the research please contact the mentor(s).

Anticipated Appointment Start Date: Summer/Fall 2021.  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 or four 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. 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 ORISE.EPA.ORD@orau.org and include the reference code for this opportunity.

Qualifications

The qualified candidate should have received a master's degree in one of the relevant fields, or be currently pursuing the degree with completion by the appointment start date. Degree must have been received within the past five years.

Preferred skills:
  • Strong written, oral and electronic communication skills
  • Proficiency in developing data science applications with R and/or Python, in the use of MySQL and NoSQL database solutions
  • Experience in bioinformatics
Eligibility Requirements
  • Citizenship: U.S. Citizen Only
  • Degree: Master's Degree received within the last 60 months or anticipated to be received by 9/30/2021 11:59:00 PM.
  • Discipline(s):
    • Chemistry and Materials Sciences (6 )
    • Computer, Information, and Data Sciences (5 )
    • Engineering (1 )
    • Environmental and Marine Sciences (2 )
    • Life Health and Medical Sciences (14 )
    • Mathematics and Statistics (4 )
    • Other Non-Science & Engineering (1 )
    • Physics (2 )
  • Veteran Status: Veterans Preference, degree received within the last 120 month(s).
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