[ascct] ORISE Fellowship in computational exposure modeling

From: Kristie Sullivan <KSullivan@xxxxxxxx>
To: "ascct@xxxxxxxxxxxxx" <ascct@xxxxxxxxxxxxx>
Date: Thu, 11 Sep 2014 01:06:54 -0400

Developing Computational Tools to Rapidly Predict Internal
Doses<http://orise.orau.gov/science-education/internships-scholarships-fellowships/description.aspx?JobId=17072>
Research Participation Program
Office of Research and Development
National Exposure Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC
EPA-ORD/NERL-HEASD-2014-09
Project Description:

A postdoctoral research project training opportunity is currently available at
the U.S. Environmental Protection Agency’s (EPA) National Exposure Research
Laboratory (NERL). The appointment will be served with the Human Exposure and
Atmospheric Sciences Division (HEASD) in Research Triangle Park, North Carolina.

HEASD focuses on conducting research to produce high-quality methods,
measurements and models needed to understand the processes and factors that
impact relationships between environmental pollutant sources and concentration,
human exposure and dose.

The selected individual will be part of an EPA team of investigators who are
addressing critical gaps in rapidly predicting exposures and internal doses of
manufactured chemicals, assessing exposures and internal doses across the life
cycle of chemicals and products, and comparing predicted doses to in vitro
toxicity data in the Chemical Safety for Sustainability (CSS) research program.
More specifically, s/he will be addressing critical gaps in accessible tools
and metrics for efficiently and effectively quantifying exposures and risks to
human health across the life cycle of manufactured chemicals.

The participant will perform research on the development and application of
computational dosimetry modeling for more rapid and higher throughput internal
dose estimation for a wide range of manufactured chemicals. Research that
includes developing approaches to link existing rapid exposure models and
computational dosimetry models is of great interest. A specific area of
interest is estimating exposures and doses across the life cycle of chemicals
and products that can facilitate the use of analytics that support
sustainability and alternative assessment considerations in chemical risk
management decision-making.

Through this project, the participant will learn to apply his/her knowledge and
skills in computational modeling to develop dosimetry models (e.g.,
physiologically based pharmacokinetic models) to link exposures across relevant
time frames and populations with internal doses, and these doses with
perturbations of normal biology leading to adverse health effects. S/he will
have the opportunity to learn about exposure sciences, pharmacokinetics,
biology, toxicology, computational modeling, data mining/management and life
cycle assessment.

The participant may have the opportunity to attend conferences and present
research findings, and/or meet with both government and academic scientists and
staff for collaboration on research and report writing. S/he will be encouraged
to publish research findings and give oral presentations to internal and
external audiences.

Qualifications:

Applicants must have received a doctoral degree in computational science,
applied mathematics, statistics, chemical engineering, environmental
engineering, biological sciences, toxicology, or a related discipline within
five years of the desired starting date, or completion of all requirements for
the degree should be expected prior to the starting date. Experience with at
least one programming/scripting language (e.g., MATLAB, Java, Python, C,
Fortran) is desired.

The program is open to all qualified individuals without regard to race, sex,
religion, color, age, physical or mental disability, national origin, or status
as a Vietnam era or disabled veteran. U.S. citizenship or lawful permanent
resident status is preferred (but a candidate also may hold an appropriate visa
status; an H1B visa is not appropriate). Guidelines for non-U.S. citizens may
be found athttp://orise.orau.gov/epa/applicants/immigration.htm.

The appointment is full time for one year and may be renewed upon
recommendation of EPA and contingent on the availability of funds. The
participant will receive a monthly stipend. Funding may be made available to
reimburse the participant's travel expenses to present the results of his/her
research at scientific conferences. No funding will be made available to cover
travel costs for pre-appointment visits, relocation costs, tuition and fees, or
a participant's health insurance. The participant must show proof of health and
medical insurance. The participant does not become an EPA employee.

Technical Questions:

The mentor for this project is Cecilia Tan
(tan.cecilia@xxxxxxx<mailto:tan.cecilia@xxxxxxx>).

How to Apply:

An application can be found at
http://orise.orau.gov/epa/applicants/application.htm. Please reference Project
# EPA-ORD/NERL-HEASD-2014-09 when calling or writing for information.

[ascct] ORISE Fellowship in computational exposure modeling

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