PhD in Computational Ecosystem Science: Carbon and nutrient cycle dynamics
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 a PhD student.
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
- Address a high-profile research challenge for a better understanding of global environmental change and climate change impacts
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.
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 look forward to receiving your online application 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 email 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.
For further information about the project, please visit the website stineb.github.io/mind. Questions regarding the position should be directed to Prof. B. Stocker by email: firstname.lastname@example.org (no applications) or phone +41 44 632 48 90.