UCLA is a major research university with the Faculty of Arts and Sciences, Medical School, and Engineering School all on the same campus, allowing access to myriad researchers and resources that could be useful to this project. UCLA is consistently in the top 5 in terms of federal research funding awarded to universities. Los Angeles is a vibrant, diverse city with outdoor activities available nearby, including beaches and mountains. L.A. also has a wide array of arts and culture, including world-class museums, theater, music, and of course, movies. Candidates are expected to be independent, highly motivated problem solvers who communicate well and enjoy working in a collaborative environment. The ideal candidate would have a background in mathematical modeling, knowledge of plant traits and trait-based models, and experience with programming languages such as Matlab, IDL, ArcGIS, R, Mathematica, C, and Python. Applicants with only a subset of these skills are encouraged to apply. Applications and any questions should be sent to <mailto:[email protected]>[email protected]. The application should include a Curriculum Vitae that details education, past research, and publications. Applicants should also submit a cover letter that describes their interest in the project and the names of three references. Review of applications will begin immediately and continue until the position is filled. UCLA is an AA/EOE that is strongly committed to diversity and excellence among its researchers.
A post-doctoral position is available (start date flexible, can start
as early as January, 2016) in the group of Dr. Van Savage
(<http://faculty.biomath.ucla.edu/vsavage/>http://faculty.biomath.ucla.edu/vsavage/)
in the Department of Ecology and Evolutionary Biology at UCLA. This
position will be supported by a recently awarded NSF grant and will
involve collaboration with researchers at Oxford University,
University of Arizona, and the Carnegie Department of Global Ecology
at Stanford University. Savage combines mathematical models with
analysis of large datasets to uncover insights into biological
systems. The project has the potential to involve theory development
for trait-based models, analysis of large datasets for plant traits
based on LIDAR, hyper-spectral, and field measurements, as well as
numerical simulations for how plant traits determine forest dynamics,
carbon production, and impacts of drought and climate change in the
Amazon. Results from this project will help lead to a deeper
understanding of how individual plant traits influence ecosystems and
also to project future productivity, diversity, and distributions of
trees in the Amazon. Savage will mentor the postdoc in designing and
conducting research projects, writing papers, giving talks, and
applying for jobs.
