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<b>Post-Doc Research Fellowship at Cornell University </b><b><br>
</b> <br>
Multi-Scale Air Quality -- Health Risk Modeling and Management
Optimization <br>
<br>
A postdoctoral research opportunity in Multi-Scale Air Quality --
Health Risk Modeling and <br>
Management Optimization is currently available for motivated,
post-graduate (PhD) interested <br>
in being part of a collaborative, interdisciplinary research with
the Cornell University <br>
Transportation and Environment/Energy Systems (CUTES) Group. The
CUTES group is a <br>
cross-disciplinary research team that takes innovative systems
informatics-analytics approaches <br>
to solving infrastructure and its associated
environment/health/economics and management <br>
problems. The Group involves faculty and grad/undergrad students
from Civil and <br>
Environmental Engineering, Statistics, Computer Science, Applied
Economics and Management, <br>
Systems Engineering, and Earth and Atmospheric Science. Research
projects in the Group <br>
expose researchers to solving the infrastructure-related
environment/health problems by focusing <br>
on the nexus of infrastructure, air quality, health risks, and
climate change concerns. The <br>
appointment will be served with the School of Civil and
Environmental Engineering at Cornell <br>
University in Ithaca NY, with potential interactions with other
Cornell units including: Atkinson <br>
Center for a Sustainable Future (ACSF,
<a class="moz-txt-link-freetext" href="http://www.acsf.cornell.edu/">http://www.acsf.cornell.edu/</a>), Cornell NYC Tech <br>
(<a class="moz-txt-link-freetext" href="http://tech.cornell.edu/">http://tech.cornell.edu/</a>), Cornell Program in Infrastructure Policy
(CPIP, <br>
<a class="moz-txt-link-freetext" href="http://www.human.cornell.edu/pam/cpip/">http://www.human.cornell.edu/pam/cpip/</a>), and Cornell Institute of
Public Affairs (CIPA, <br>
<a class="moz-txt-link-freetext" href="http://www.cipa.cornell.edu/">http://www.cipa.cornell.edu/</a>), etc. <br>
CUTES research focuses on the characterization, quantification,
management optimization, and <br>
policy/strategy design for cost-effective and equitable control of
adverse health effects due to <br>
environmental pollutants from infrastructure such as transportation
and power systems. Results of <br>
this research are used to inform the public and decision makers at
local, national and international <br>
levels for infrastructure investment, planning, and operations
management, environmental <br>
assessments and plan for air quality standards and public health.
CUTES aims to formulate and <br>
conduct research designed to: 1) characterize the relationships
between infrastructure, users, air <br>
quality, climate change, and adverse health effects; 2) model the
health effects of individual <br>
major pollutants (such as ozone, nitrogen oxides, and particles) and
multipollutant mixtures; 3) <br>
assess the health implication of pollutants near sources such as
roads, ports, particularly for at-risk human populations who are
disproportionately impacted by pollution; and 4) evaluate the air <br>
quality and health impacts of environmental policies and regulation,
infrastructure policy and <br>
operations management (e.g., production and usage of alternative
energy sources such as <br>
biomass) and seek management optimization and policy design towards
green infrastructure for <br>
livable communities. <br>
This research opportunity focuses on multi-scale air quality --
health risks modeling and <br>
management optimization. The ideal applicant will have experience
with multi-scale emissions <br>
inventory estimation and air quality modeling, health risk
assessment, formulation and solution of <br>
policy optimization problems, and familiarity with the quantitative
assessment of environmental <br>
impacts of industrial/transportation activity. Excellence in
academic writing such as journal <br>
papers and research proposals is essential. Contributing to the
development of manuscripts for <br>
<br>
submission to peer-reviewed journals and presentations to describe
research methods, key <br>
findings and implications useful to inform policy-level decision
making. <br>
This will be a fantastic research experience where the post-doc
fellow will work closely with <br>
faculty and graduate students in the development of AQ-Health
modeling and management <br>
methodologies, resource/environmental economics models, computing
software, and decision <br>
supporting systems for both government policies and firm growth
strategies. The research <br>
participant will learn to: process large data sets for appropriate
modeling and analyses; and <br>
further develop skills for successful manuscript preparations and
reviews. The research <br>
participant will have the opportunity to interact with a
multidisciplinary team of engineers, <br>
scientists, and economists. The advising faculty will have close
interaction with the researchers <br>
through weekly individual meetings and research group meetings. <br>
Qualification: <br>
Applicants must have received a doctoral degree with a concentration
on or a strong experience in <br>
Air Quality and Health Risk Modeling, AQ-Health Systems Management
or Applications of <br>
Operations Research in relevant fields, or other relevant field
(with an emphasis on analytical <br>
systems modeling) within five years of the desired starting date, or
completion of all requirements <br>
for the degree should be expected prior to the starting date. <br>
Excellence in academic writing such as journal papers and research
proposals is essential. The <br>
fellow will be expected to develop and adapt AQ-Health Risk models,
mathematical/statistical <br>
methods and techniques and/or advanced modeling tools with the aim
of evaluating the <br>
environment/health impacts of infrastructure (such as
transportation) plans and relevant <br>
technologies and policies. Knowledge and experience in AQ-Health
risk modeling, <br>
scientific/engineering computing and programming, statistical and
mathematical modeling for <br>
optimization, or training in resource/environmental economics is
desired. Proficiency in certain <br>
programming language (e.g., C++/Java, Matlab, Python, etc.),
statistical analysis packages (e.g., <br>
R, SAS, SPSS, GAUSS), and ArcGIS is a plus. <br>
How to Apply: <br>
If you are interested please contact Professor H. Oliver Gao and
email your application package <br>
to: H. Oliver Gao (<a class="moz-txt-link-abbreviated" href="mailto:hg55@cornell.edu">hg55@cornell.edu</a>). An application should contain:
<br>
1. A cover letter. <br>
2. CV, include complete list of publications <br>
3. Contact information for 3 references (can be included at the end
of your CV) <br>
4. Two or three of your publications relevant to the topic <br>
5. A research statement (e.g., previous work, future research
interests and directions, and <br>
career goals, etc. 3-page maximum, single space), and <br>
6. A transcript (electronic version will be fine) <br>
For convenience, please use “Post-doc application—AQ” in the subject
line of your email, and <br>
name your documents as: “Your First Name_Last Name-CV”, “Your First
Name_Last Name-ResearchStatement”, and “Your First Name_Last
Name-Transcript”, respectively. Review of <br>
applications will start immediately and continue until the position
is filled. Start date can be as <br>
soon as possible. Initial appointment will be for one year, with
possible extensions. Salary <br>
conforms the Cornell University standard. <br>
<br>
The College of Engineering at Cornell University is an
equal-opportunity affirmative-action <br>
employer. Women and minorities are encouraged to apply. <br>
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