Job Description

About Us
The Chair of Digital Agriculture is engaged in simulation models of plant stands to improve plant system understanding and its control and optimization. Our research links Artificial Intelligence methods to topics in agriculture and spans many scales from field to global.
Project Description
Soybean is a critical crop for global food security and agricultural economies. This research project aims to develop AI-driven computer vision systems that can accurately identify plant diseases and predict plant health in soybean crops, enabling early intervention and improved crop management. You will work on developing the imaging system as well as novel machine learning approaches for image analysis and disease classification using field data from German and Brazilian agricultural trials.
Responsibilities

• Design the imaging system for generating image datasets from agricultural machines
• Develop and implement computer vision algorithms for plant disease detection and health estimation in soybeans
• Design and train deep learning models using agricultural image datasets
• Collaborate with researchers at the University of São Paulo and agricultural domain experts
• Publish research findings in peer-reviewed journals and present at international conferences

Required Qualifications

• Master's degree in computer science, or a closely related field
• Strong programming skills in Python and experience with deep learning frameworks (PyTorch, TensorFlow, or similar)
• Solid foundation in computer vision and image processing techniques
• Excellent written and oral communication skills in English
• Ability to work independently and as part of an international team

Desired Qualifications

• Familiarity with cloud computing platforms and large-scale data processing
• German language skills
• Publications in computer vision or machine learning venues
• Prior experience with agricultural applications or remote sensing

We Offer

• A fully funded PhD position for 3 years (TV-L E13)
• Opportunity to work on real-world agricultural challenges with significant impact
• International research collaboration with leading institutions
• Research-related trips to Brazil and international conferences
• Supportive research environment with experienced supervisors
• The possibility of research stays abroad

Application Materials

• Please submit the following documents:
• Curriculum vitae, including a list of publications (if applicable)
• Short cover letter describing your motivation and relevant experience
• Electronic copies of academic diplomas and relevant employment references

Application Deadline
15 January 2026
Earliest Starting Date
1 March 2026
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Skills Required