[ES_JOBS_NET] University of Michigan Postdoctoral Research Associate: Multifunctionality of Forest Ecosystems

Kai Zhu kai.zhu at alumni.duke.edu
Mon Dec 19 13:00:26 MST 2022


University of Michigan Postdoctoral Research Associate: Multifunctionality of Forest Ecosystems

We seek a postdoctoral researcher to join a collaborative team of ecologists in studying the integrated nature of forest functions that are critical for productivity, water and energy usage, and nutrient cycling. The post-doc will leverage available data from the University of Michigan Biological Station and northern Great Lakes to develop models of forest multifunctionality that include functions’ codependencies. The postdoctoral researcher will be based at the University of Michigan and collaborate with Drs. Inés Ibáñez (U. Michigan), Aimee Classen (U. Michigan), and Chris Gough (Virginia Commonwealth U.).

We seek candidates with a Ph.D. in ecology or closely related field.  Expertise with statistical modeling and data processing is required.  The initial appointment period will be for 1 year with the potential of renewal.

Applicants should email inquiries and applications (a cover letter describing research experience and goals, a curriculum vitae, reprints, and the names and addresses of three references) to Dr. Inés Ibáñez (iibanez at umich.edu) School for Environment and Sustainability, University of Michigan, Ann Arbor. The University of Michigan is a non-discriminatory, affirmative-action employer.

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Kai Zhu, PhD
Associate Professor
Institute for Global Change Biology
School for Environment and Sustainability
University of Michigan
https://zhulab.seas.umich.edu
[http://zhulab.seas.umich.edu/wp-content/uploads/SEAS-logo-400.png]<https://zhulab.seas.umich.edu/>
Zhu Lab @ SEAS – Global Change Biology<https://zhulab.seas.umich.edu/>
We are global ecologists and quantitative environmental scientists, interested in the intersection of climate change, biodiversity, and ecosystem processes. The goal at Zhu Lab Is to merge observations, experiments, and models to inform new knowledge in global change. We use interdisciplinary
zhulab.seas.umich.edu

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