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European Geosciences Union

PhD in Computational Ecosystem Science: Carbon-nutrients dynamics

PhD in Computational Ecosystem Science: Carbon-nutrients dynamics

ETH Zürich logo

ETH Zürich

Our group for Computational Ecosystem Science develops new model and data integration methods to gain a mechanistic understanding of biogeochemical cycling in ecosystems, water-carbon coupling, and forest responses to climate change. We are co-hosted at the ETH Institute of Agricultural Sciences and the WSL Unit Forest Dynamics and work at the intersection of Earth system science, ecophysiology, ecology, applied statistics, and high-performance computing. Within the Swiss National Science Foundation project MIND – Next-generation modelling of the biosphere: Including new data streams and optimality approaches, we are recruiting for spring 2020.


Zürich, Switzerland


Relevant divisions
Biogeosciences (BG)
Earth and Space Science Informatics (ESSI)
Soil System Sciences (SSS)

Full time

Entry level

40000 - 45000 € / Year, 1st year: 47700 CHF, 2nd year: 48540, 3rd and 4th year: 50040

Required education

Application deadline
13 January 2020

21 November 2019

Job description

You will develop new methods to simulate processes by which nutrient limitation affects plant growth, allocation, and ecosystem dynamics. Unknown long-term effects of carbon-nutrient cycle and plant-soil interactions and a lack of appropriate models are a major contributor to uncertainty in climate change and CO2 projections. Your aim will be to extend a database of observations from ecosystem experiments and plant trait measurements, to develop new modelling approaches based on eco-evolutionary optimality principles, and to implement an integration of observations into model predictions. Thus, you will contribute to the development of a next-generation vegetation model.

This position requires independent and creative thinking to formulate hypotheses; critically assess the science at the intersection of biogeochemistry, terrestrial ecology and Earth system sciences; develop novel modelling methods; and to address a high-profile research challenge for a better understanding of global environmental change and climate change impacts.
The candidate must hold a M.Sc. degree in natural sciences, mathematics, or engineering and should demonstrate proficient English written and oral skills and excellent analytical and numerical skills. Experience with programming and other data science methods are an asset and an open and collaborative mentality for the development of our computational infrastructure is expected.
We offer the candidate to be part of a small group with a strong collaborative philosophy and to benefit from a world-leading academic environment, from an international collaboration within the project and from the excellent quality of life in Switzerland.

For further information about the project please visit the website Questions regarding the position should be directed to Prof. B. Stocker by email: (no applications) or phone +41 44 632 48 90.

How to apply

We look forward to receiving your online application through

before 13 January 2020 including the following documents: Motivation letter (max. 2 pages, with a statement of research interests), a CV, copies of academic qualifications and the names and e-mail addresses of three referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.