Hugo Storm
5 months ago
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PhD in Agricultural Economics and Data Science for Farm Diversification and Management Complexity University of Bonn in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
PhD position within the DFG-funded Collaborative Research Center FoodDiverse (CRC 1780). The broader CRC offers excellent research conditions and includes 24 doctoral researchers and 8 postdoctoral researchers; no stipend amount or tuition details are stated in the post excerpt.
Deadline
Expired
Country
Germany
University
University of Bonn

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About this position
PhD opening in Agricultural Economics and Data Science at the University of Bonn in the group Data science in Agricultural Economics led by Hugo Storm. The position is part of Project A05 in the new Collaborative Research Center FoodDiverse (CRC 1780), funded by the German Research Foundation (DFG).
The project studies how different types and degrees of agricultural diversification affect farm labor requirements, management complexity, managerial control, and resource-use efficiency. The empirical focus is on Germany and Ghana, using farm survey data and hybrid modeling approaches that combine economic theory with modern data science.
Research methods and interests highlighted in the post include Bayesian probabilistic programming, probabilistic machine learning, deep learning, and econometric analysis. This is a strong fit for candidates interested in the intersection of agricultural economics, statistics, computer science, and sustainability-oriented food systems research.
The broader FoodDiverse CRC offers excellent research conditions and includes multiple doctoral and postdoctoral positions across related projects. Applications are welcome until 2026-06-14. The application portal and further instructions are available on the FoodDiverse website.
Funding details
PhD position within the DFG-funded Collaborative Research Center FoodDiverse (CRC 1780). The broader CRC offers excellent research conditions and includes 24 doctoral researchers and 8 postdoctoral researchers; no stipend amount or tuition details are stated in the post excerpt.
What's required
Applicants should be interested in agricultural economics and data science, with motivation to work on farm diversification, management complexity, and resource-use efficiency. The project emphasizes Bayesian probabilistic programming, probabilistic machine learning, hybrid modeling, and combining theory-based economic concepts with flexible deep learning methods. The post is for doctoral researchers; no additional formal requirements are stated in the post excerpt.
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