PhD Candidate in Forest Ecology

WorkplaceZurich, Zurich region, Switzerland


The Forest Ecology Group at ETH Zurich is a dynamic interdisciplinary research team that examines both theoretical and applied questions in forest ecology using a combination of empirical and modeling techniques. The overarching aim of the group is to further our understanding of the structure and function of forest ecosystems, with a particular focus on mountain areas such as the European Alps. We offer world-class facilities in a relaxing work atmosphere with lots of opportunities for collaboration both within and beyond our group. The Forest Ecology group seeks to appoint per 1 July 2018 (initial contract for one year; an extension by three years is foreseen) or by mutual agreement a

to work on a project related to climate dynamics, tree phenology and dendrochronology. The project is funded by the Swiss National Science Foundation ("Assessing climate impacts on tree phenology and growth rates: combining phenological observations with tree-ring data"). Global warming has resulted in shifts of leaf phenology and late spring frost events. However, there is little evidence whether an extended growing period or shifts in spring frost translate into changed tree growth rates. The goal of the project is to link observed dates of leaf unfolding and leaf coloring from the phenological network of MeteoSwiss with daily weather data and tree-ring series of various species.

The PhD candidate will statistically analyze data of leaf unfolding and leaf coloring of trees, tree-ring data and daily weather data. The PhD candidate will further plan and conduct field work at multiple sites in Switzerland to sample increment cores of trees and take additional measurements. The results of the thesis will be published in international scientific journals.

The candidate should have an MSc degree in ecology, environmental sciences, forest sciences, forestry, geography, biology, or a related field. Candidates should have experience or at least a strong interest in doing dendrochronological field and lab work. A background in statistical data analysis, experience with the statistical computing language R and knowledge of forest ecology are strong assets. Candidates should be communicative and have a good command of English and German (French and Italian are beneficial). A driving licence is an asset.

In your application, please refer to
and reference  JobID 39376.

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