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Wetsus

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PhD in AI-driven soil insight and precision management using weed indicators Wetsus in Netherlands

Degree Level

PhD

Field of study

Computer Science

Funding

PhD project opening; funding details are not specified in the post. The position appears to be a standard doctoral vacancy within the Wetsus/Leiden University project.

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Country

Netherlands

University

Wetsus

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Keywords

Computer Science
Environmental Science
Agriculture
Biology
Earth Science
Soil Ecology
Statistics
Precision Farming
Plant-soil Interaction
ML

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About this position

PhD opportunity at Wetsus / Leiden University in AI-driven soil insight and precision management using weed indicators.

This project sits at the intersection of agriculture, environmental science, biology, computer science, and statistics. The research explores how weed plant communities can act as practical bio-indicators of soil status in agricultural fields. By combining proximal sensing, field spectroscopy, GIS, plant trait analysis, soil measurements, and microbiome data, the project aims to build a non-destructive framework for soil characterization and field heterogeneity mapping.

You will work on extracting quantitative plant traits from spectral and imaging data, analysing soil physicochemical and microbiome datasets, and developing interpretable machine learning models that infer soil conditions from weed indicators. A major focus is model transparency: the project explicitly seeks to identify which species, traits, and trait–soil interactions drive predictions. The work also investigates plant–soil feedbacks and whether weed characteristics can help forecast crop performance, disease risk, and abiotic or biotic stress.

The position involves interdisciplinary experimentation, field campaigns, data analysis, and predictive modelling. Expected outcomes include spatial decision-support tools that could help farmers estimate soil variability through weed observations, reduce sampling effort, and support targeted soil management, crop protection, and rotation planning.

Eligibility highlights: a master’s degree in soil sciences, plant sciences, environmental sciences, geo-information sciences, data sciences, or a related quantitative/ecological field; experience with field sampling and data analysis/statistical modelling; machine learning, GIS, or spectral data analysis are advantageous. A driver’s license and Dutch language ability are a plus.

Supervision: University promotor Prof. Dr. Martijn Bezemer (Institute of Biology, Leiden University), with Wetsus supervisors Dr. Jiahui Gu and Dr. Mohamed Zakaria Hatim.

Application: complete applications in English must be submitted via the application webpage before the deadline. See the applicant guidelines for details.

Funding details

PhD project opening; funding details are not specified in the post. The position appears to be a standard doctoral vacancy within the Wetsus/Leiden University project.

What's required

Applicants should hold a master's degree in soil sciences, plant sciences, environmental sciences, geo-information sciences, data sciences, or a related discipline combining quantitative methods with ecological or agricultural sciences. Experience with soil or vegetation field sampling and data analysis/statistical modelling is expected. Familiarity with machine learning methods, GIS, or spectral data analysis is an advantage. The post also notes that a driver’s license and ability to communicate in Dutch are a plus.

How to apply

Apply via the application webpage before the deadline. Only complete applications submitted in English will be considered eligible. Review the applicant guidelines before submitting.

More information can be found here

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