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Post-doctoral position: Improving understanding and modeling of tropical forest carbon uptake in a <br>
changing climate<br>
<br>
The Terrestrial Ecosystem Science and Technology (TEST) group (<a href="http://www.bnl.gov/TEST/">http://www.bnl.gov/TEST/</a>) at <br>
Brookhaven National Laboratory is seeking a post-doc interested in understanding and reducing <br>
model uncertainty associated with projecting the response of tropical forest ecosystems to global <br>
change. The successful candidate will work closely with Drs. Serbin and Rogers to: 1) assemble a <br>
comprehensive database of plant traits associated with modeling carbon assimilation and respiration <br>
in tropical forest ecosystems, 2) develop an independent multi-assumption, multi-scale, mechanistic <br>
description of canopy physiology and 3) identify the key modeling assumptions and parameters that <br>
lead to variability in model projections of the response of tropical forests to rising temperature and <br>
carbon dioxide concentration. The successful candidate will be part of a multidisciplinary, multi-<br>
institutional project (NGEE-Tropics) - led by Lawrence Berkeley National Laboratory - that brings <br>
together a team of scientists seeking to improve the representation of tropical forest ecosystems in <br>
Earth System Models.<br>
<br>
The essential duties and responsibilities of the post-doc include-<br>
<br>
Data curation, synthesis and management<br>
Integrate and run existing process models within an uncertainty quantification environment<br>
Computer programming and modifications to existing model code<br>
The development, testing, and application of key submodels of carbon uptake and respiration<br>
Publish results in peer-review journals and present at scientific conferences<br>
<br>
Prospective candidates should have-<br>
<br>
Ph.D. in computer science, plant biology, ecosystem ecology, ecophysiology, or related field<br>
Computer programming experience<br>
Willingness to work collaboratively in team environments<br>
Effective written and oral communication skills<br>
Record of publication in high quality internationally recognized journals<br>
Preferred Knowledge, Skills, and Abilities:<br>
Experience with programming in Fortran, C-based languages, Python, and R, including the ability to <br>
work within version control and community development frameworks (e.g. GitHub)<br>
Experience working within Linux and High-performance computing (HPC) environments<br>
Background in plant biochemistry, physiology, and ecology with a focus on photosynthesis, <br>
respiration , and allocation<br>
Experience using numerical simulation models to predict carbon fluxes and stocks<br>
Experience working within model-data assimilation and uncertainty quantification frameworks<br>
<br>
Application Process-<br>
<br>
Applicants should visit the BNL Careers website (<a href="http://www.bnl.gov/HR/careers/">http://www.bnl.gov/HR/careers/</a> ) and search for Job <br>
#181 to apply. Review of applications begins on February 2nd, 2015 and the position will remain <br>
open until a suitable candidate is identified. Our preferred start date is April 1st, 2015.<br>
<br>
Brookhaven National Laboratory (BNL) is an equal opportunity employer committed to ensuring that <br>
all qualified applicants receive consideration for employment and will not be discriminated against on <br>
the basis of race, color, religion, sex, sexual orientation, national origin, age, disability, or protected <br>
veteran status. BNL takes affirmative action in support of its policy and to advance in employment <br>
individuals who are minorities, women, protected veterans, and individuals with disabilities.
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