The Max Planck Institute for Biogeochemistry (MPI-BGC) in Jena is dedicated to interdisciplinary fundamental research in the field of Earth system sciences with a focus on climate and ecosystems. The internationally renowned institute, which currently employs around 250 people, celebrated its 25th anniversary in 2022. Jena is known for high-tech industry, internationally renowned research institutions and a modern university, but it also has a beautiful natural setting in the green Saale valley with steep limestone slopes. The city of Jena has an active student scene and a diverse cultural life.

We are seeking a PostDoc for Integrated subsurface hydrology-vegetation modelling (m/f/d) in full time/part time possible; fix term position for 2 years.

Background and position description

The "Machine Learning for Hydrological and Earth Systems" group within the Department of Biogeochemical Integration at the Max Planck Institute for Biogeochemistry is looking for a highly motivated postdoctoral researcher. This position is part of the CZS-funded project “Knowledge Integration for Spatio-temporal Environmental Modelling.” The research will focus on an integrated modelling framework that combines process-based hydrological models (e.g., considering hillslope topography and subsurface flow), ecosystem dynamics models, and hybrid machine learning tools. The ultimate goal of the project is to improve our understanding of how topography and subsurface hydrological processes modulate the impacts of climate change on vegetation dynamics and the water cycle. A key aspect of this work will be to consider the hybrid modelling approach to assimilate different data sources (e.g., satellite-derived vegetation structure, soil moisture, and flux observations) to validate, calibrate, and refine the integrated modelling system. The project aims to address questions such as what are the key processes governing water storage and vegetation water sourcing along topographic gradients.
This position is embedded in the Machine Learning for Hydrological and Earth Systems group Machine Learning for Hydrological and Earth Systems group in the Department of Biogeochemical Integration. We emphasize the combination of advanced data-driven techniques with classical Earth system analysis to improve modelling and understanding of complex dynamics among interconnected Earth subsystems. For us, machine learning serves as both a bridge and a lens, connecting extensive Earth datasets to underlying system dynamics. Our group is particularly interested in the interactions between vegetation and hydroclimate across multiple scales. We seek to understand how shifting hydrological patterns regulate ecosystem responses to environmental change, and how terrestrial ecosystems, in turn, can feedback into hydroclimate systems and influence extreme events.
The position offers early-career scientists an excellent opportunity to further develop professional competencies and advance their research record. The successful candidate will engage in interdisciplinary collaborations within the department and participate in the ELLIS Unit Jena network, fostering expertise in machine learning and Earth system sciences. The position provides access to state-of-the-art computational resources, modern research infrastructure, and a well-equipped office environment.

Your tasks

• Develop and apply integrated modelling frameworks to study subsurface hydrology, plant water use, and ecosystem responses
• Analyse and assimilate spatially resolved datasets (e.g., satellite observations of vegetation structure and soil moisture) to improve model accuracy and predictive capabilities
• Investigate how topography and subsurface hydrological processes mediate climate change impacts on vegetation dynamics and the water cycle
• Disseminate research findings through peer-reviewed publications and presentations at international conferences
• Assist in the supervision of doctoral researchers, contributing to their academic and professional development

Your profile

• A PhD in ecohydrology, hillslope hydrology, environmental science, Earth system science, biogeosciences, climate science, or a related field
• Expertise in hydrological and ecological modeling approaches or land surface models
• Experience in hybrid and explainable machine learning methods is an advantage
• Proficiency in programming and analysis tools such as Python, R, or MATLAB
• Experience in publishing scientific papers, preferably on topics such as ecohydrology, water-carbon coupling, hillslope hydrology, or AI-powered environmental analytics
• Strong teamwork and collaboration skills, with a responsible and proactive attitude
• Ability to work both independently and as part of a team
• Excellent communication skills (oral and written) in English

Our offer

The position is scheduled to start on May 01, 2025, with the possibility for a slightly later start date to be negotiated. The current two-year term of the position may be extended based on funding opportunities. Part-time work is generally possible. The position will be evaluated and graded following the collective agreement according to TVöD Bund; in addition, we will provide a pension plan based on the public service (VBL).
The Max Planck Society (MPS) strives for gender equality and diversity. The MPS aims to increase the proportion of women in areas where they are underrepresented. Women are therefore explicitly encouraged to apply. We welcome applications from all fields. The Max Planck Society has set itself the goal of employing more severely disabled people. Applications from severely disabled persons are expressly encouraged.

Your application

Any further inquiries about the position and/or expectations are most welcome and can be directed to Dr. Shijie Jiang: sjiang@bgc-jena.mpg.de

Are you interested? Please send us your application with cover letter, curriculum vitae as well as names and contact information of two references summarised in a PDF file (max. 10 MB) by e-mail to bewerbung@bgc-jena.mpg.de or to the

Max-Planck-Institut für Biogeochemie
Personalbüro: Kennwort “Postdoc 24/2024”
Hans-Knöll-Straße 10
07745 Jena

by February 13, 2025, quoting the reference number 24/2024. We ask that you do not use application folders, but only submit copies, as your documents will be destroyed in accordance with data protection regulations after the application process has been completed.

We look forward to receiving your application!