University of Göttingen
2 months ago
PhD in Crop Modelling and Plant Stress Physiology at Georg-August University Göttingen Georg-August University Göttingen in Germany
Degree Level
PhD
Field of study
Environmental Science
Funding
The position is a 4-year fully funded PhD scholarship, covering living expenses and providing access to high-performance computing and unique datasets. No specific stipend amount or tuition coverage details are mentioned.
Deadline
Expired
Country
Germany
University
University of Göttingen

How do Korean students apply for this?
Sign in for free to reveal details, requirements, and source links.
Where to contact
Keywords
About this position
The Faculty of Agricultural Sciences at Georg-August University Göttingen in Germany is offering a 4-year fully funded PhD position in process-based crop modelling, focusing on biotic–abiotic stress interactions in maize. This opportunity is part of the DFG-funded Research Unit MultiStress, which investigates how maize responds to combined biotic (such as Setosphaeria turcica) and abiotic (drought, nitrogen deficit) stress factors. The successful candidate will develop new routines to describe disease impacts on maize, integrate and test models within the MultiStress system, calibrate models using field data, and analyze how various stresses affect yield and quality. The project involves collaboration across experimental, modelling, and synthesis subprojects, and offers the chance to publish in international peer-reviewed journals.
Applicants should have a Master’s degree in Crop Science, Agronomy, Plant Pathology, Environmental Sciences, Systems Biology, or a related field. Essential skills include a strong interest in quantitative crop modelling, proficiency in R or Python, and data analysis. Experience with process-based crop models is advantageous. Excellent English communication skills and the ability to work independently in an interdisciplinary, international team are required.
The position provides a dynamic, international research environment, excellent supervision and training opportunities, access to unique multi-stress datasets, high-performance computing resources, and opportunities for international exchange. The PhD scholarship is fully funded for four years. The application deadline is 04 January 2026, with interviews scheduled for mid-January 2026. To apply, candidates should submit a single PDF containing a motivation letter, CV, and certificates via email to Prof. Dr. Reimund Rötter ([email protected]). For further information, Dr. Munir Hoffmann ([email protected]) can also be contacted.
This is an excellent opportunity for those passionate about crop modelling, plant stress physiology, and interdisciplinary agricultural research to join one of Europe’s leading agricultural science institutions. Keywords: crop modelling, plant stress physiology, maize, biotic stress, abiotic stress, process-based models, agronomy, plant pathology, environmental sciences, systems biology.
Funding details
The position is a 4-year fully funded PhD scholarship, covering living expenses and providing access to high-performance computing and unique datasets. No specific stipend amount or tuition coverage details are mentioned.
What's required
Applicants must hold a Master’s degree in Crop Science, Agronomy, Plant Pathology, Environmental Sciences, Systems Biology, or a related field. They should have a strong interest in quantitative crop modelling, skills in R or Python and data analysis, and experience with process-based crop models is an advantage. Excellent English communication skills and the ability to work independently in an interdisciplinary, international team are required.
How to apply
Submit a single PDF containing your motivation letter, CV, and certificates via email to [email protected]. Ensure your application is complete before the deadline. Interviews will be held in January 2026. Contact the supervisors for further information.
Ask ApplyKite AI
Professors

How do Korean students apply for this?
Sign in for free to reveal details, requirements, and source links.