Doctoral Position in Hybrid Forest Modeling at the University of Freiburg 2026

The CRC 1537 - ECOSENSE invites applications for a doctoral researcher position at the Chair of Biometry and Environmental System Analysis Doctoral position in Hybrid Forest Modeling.

Within ECOSENSE, you will combine process knowledge, empirical data, and machine learning to improve dynamic forest modeling for prediction and inference. You will contribute to the development of a novel hybrid modeling framework (Forest Informed Neural Networks, FINN) by developing, training, and testing a hybrid forest growth model based on ECOSENSE data (Photosynthesis, Sap Flow, GPP, Volatile Organic Compounds (VOCs), soil variables, remote sensing, tree growth, etc.).

Table of Content

• Summary
• Benefits
• Requirements
• Application Deadline
• How To Apply

Summary

• Application DeadlineApril 15, 2026
• Study LevelPhD
• SponsorUniversity of Freiburg
• City to studyBaden-Württemberg
• School to studyUniversity of Freiburg
• Eligible CountryAll Countries

Benefits

• An exciting interdisciplinary topic with a high impact socio-ecological impact
• A salary according to TV-L E13 (75%)
• Contracts will initially run for three years with an option of extension until the end of the CRC’s second phase, which will be June 2030.
• Modern laboratory equipment and a highly qualified, multicultural team, which will cooperate with you and support you along your professional growth.

Requirements

• You hold a Master’s degree in environmental sciences, forest science, biology, computer sciences, or any other field related to modeling, machine learning, or ecology. If already available, please include your M.Sc. thesis in your application.
• Basic knowledge of tree physiology and plant ecology.
• Familiarity with fundamental concepts of forest dynamics such as succession trajectories and demographic processes.
• Some experience of process modeling, ideally with forest models, and model evaluation.
• Basic knowledge of Statistical Methods (e.g., Generalized Linear Models, Bayes’, Process Modeling) and experience in one programming language commonly used in data science (e.g. R and/or Python).
• Ability to harmonize and analyze diverse data sets.
• Ability to work independently and strong communication skills for collaborating with other ECOSENSE researchers.
• Excellent English skills.
• Great enthusiasm for working in a large interdisciplinary project and interest in collaborative research.
• Driver’s license is a plus.

Check also:
2026 Fully Funded Humboldt Research Fellowship
2026 Konrad Adenauer Foundation Scholarship

Application Deadline

How To Apply

• For more information kindly visit the University of Freiburg webpage.