Publisher
source

Nina Buchmann

2 weeks ago

Postdoc on Partitioning Forest CO2 and Water Vapour Fluxes ETH Zürich in Switzerland

Degree Level

Postdoc

Field of study

Environmental Science

Funding

Available

Deadline

Apr 1, 2026

Country flag

Country

Switzerland

University

ETH Zürich

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Where to contact

Official Email

Keywords

Environmental Science
Biology
Earth Science
Stable Isotope
Machine learning

About this position

The Grassland Sciences group at ETH Zurich, part of the Department of Environmental Systems Science, invites applications for a postdoctoral position focused on partitioning forest CO2 and water vapour fluxes. This research is embedded in the INETFLUX project, a collaboration between ETH Zurich, WSL (Dr. Roman Zweifel), and CzechGlobe, aiming to develop innovative technologies to disentangle carbon dioxide and evapotranspiration fluxes in forests. The project seeks to advance process- and system-understanding of biosphere-atmosphere greenhouse gas exchange, particularly in response to management and climate.

The successful candidate will develop knowledge-guided machine learning approaches (including XGBoost and SHAP analyses) to partition net ecosystem CO2 fluxes and evapotranspiration into gross primary production, ecosystem respiration, transpiration, and evaporation. The research will leverage existing tree dendrometer and sap flow measurements, as well as stable isotopes in tree rings, to provide additional constraints. Forest sites are located in Switzerland and the Czech Republic, and the candidate will be responsible for one eddy-covariance flux station within the Swiss FluxNet.

Key responsibilities include identifying environmental drivers and their temporal development to understand forest responses to climate and extreme events, compiling tree dendrometer and sap flow data, presenting results, publishing findings, and participating in a 3-month stage at CzechGlobe. The role also involves knowledge exchange and capacity building within the project, including workshops, training visits, and co-supervision of doctoral students.

Applicants must hold a PhD or doctoral degree with a strong research background in micrometeorology, greenhouse gas exchange, tree and/or ecosystem physiology. Experience in observations, modelling, or statistical analyses is required, along with excellent skills in large data analyses and proficiency in English. A driver’s license is mandatory, and experience in knowledge exchange and student supervision is advantageous.

The position is funded for up to three years, with salary and social benefits provided according to ETH Zurich rules. ETH Zurich offers numerous benefits, including public transport season tickets, car sharing, sports facilities, childcare, and attractive pension benefits. The university values diversity, sustainability, and an inclusive culture, promoting equality of opportunity and a climate-neutral future.

Applications must be submitted online via the ETH Zurich application portal by 1 April 2026. Required documents include a letter of motivation, CV with publication list, transcripts of Bachelor's, Master's, and PhD/doctoral studies, and contact information for two referees. The envisaged starting date is 1 July 2026 or upon agreement. For further information about the Grassland Sciences group, visit the group website. Questions regarding the position can be directed to Prof. Dr. Nina Buchmann at [email protected] (no applications via email).

ETH Zurich is a leading university in science and technology, renowned for excellent education, cutting-edge research, and direct transfer of new knowledge into society. With over 30,000 people from more than 120 countries, ETH Zurich fosters independent thinking and excellence, working together to address global challenges.

Funding details

Available

What's required

Applicants must hold a PhD or doctoral degree with a strong proven research background in micrometeorology, greenhouse gas exchange, tree and/or ecosystem physiology. Relevant research experience can be based on observations, modelling or statistical analyses. Excellent command of large data analyses as well as very good English language skills are mandatory. Driver’s license is required. Experience in knowledge exchange and student supervision is a plus.

How to apply

Submit your application online via the ETH Zurich application portal by 1 April 2026. Include a letter of motivation, CV with publication list, transcripts of Bachelor's, Master's, and PhD/doctoral studies, and contact information of two referees. Applications via email or postal services or incomplete applications will not be considered.

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