[ECOLOG-L] Post-doc: modeling tropical carbon uptake in a changing climate

Post-doctoral position: Improving understanding and modeling of tropical forest carbon uptake in a
changing climate

The Terrestrial Ecosystem Science and Technology (TEST) group (http://ift.tt/1GF9iEe) at
Brookhaven National Laboratory is seeking a post-doc interested in understanding and reducing
model uncertainty associated with projecting the response of tropical forest ecosystems to global
change. The successful candidate will work closely with Drs. Serbin and Rogers to: 1) assemble a
comprehensive database of plant traits associated with modeling carbon assimilation and respiration
in tropical forest ecosystems, 2) develop an independent multi-assumption, multi-scale, mechanistic
description of canopy physiology and 3) identify the key modeling assumptions and parameters that
lead to variability in model projections of the response of tropical forests to rising temperature and
carbon dioxide concentration. The successful candidate will be part of a multidisciplinary, multi-
institutional project (NGEE-Tropics) – led by Lawrence Berkeley National Laboratory – that brings
together a team of scientists seeking to improve the representation of tropical forest ecosystems in
Earth System Models.

The essential duties and responsibilities of the post-doc include-

Data curation, synthesis and management
Integrate and run existing process models within an uncertainty quantification environment
Computer programming and modifications to existing model code
The development, testing, and application of key submodels of carbon uptake and respiration
Publish results in peer-review journals and present at scientific conferences

Prospective candidates should have-

Ph.D. in computer science, plant biology, ecosystem ecology, ecophysiology, or related field
Computer programming experience
Willingness to work collaboratively in team environments
Effective written and oral communication skills
Record of publication in high quality internationally recognized journals
Preferred Knowledge, Skills, and Abilities:
Experience with programming in Fortran, C-based languages, Python, and R, including the ability to
work within version control and community development frameworks (e.g. GitHub)
Experience working within Linux and High-performance computing (HPC) environments
Background in plant biochemistry, physiology, and ecology with a focus on photosynthesis,
respiration , and allocation
Experience using numerical simulation models to predict carbon fluxes and stocks
Experience working within model-data assimilation and uncertainty quantification frameworks

Application Process-

Applicants should visit the BNL Careers website (http://ift.tt/1mvxAd1 ) and search for Job
#181 to apply. Review of applications begins on February 2nd, 2015 and the position will remain
open until a suitable candidate is identified. Our preferred start date is April 1st, 2015.

Brookhaven National Laboratory (BNL) is an equal opportunity employer committed to ensuring that
all qualified applicants receive consideration for employment and will not be discriminated against on
the basis of race, color, religion, sex, sexual orientation, national origin, age, disability, or protected
veteran status. BNL takes affirmative action in support of its policy and to advance in employment
individuals who are minorities, women, protected veterans, and individuals with disabilities.

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