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Open nowPosted 26 days ago

Professor/University

EURES job mobility portal370,340 open roles

Where
Noord-Friesland, Netherlands
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Your applicationOpen nowProfessor/UniversityEURES job mobility portal · Noord-Friesland, Netherlands

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. EURES job mobility portal postings stay open a median of 3 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.2%30 days
This job: posted 26 days ago

EURES job mobility portal median: 3 days open

The posting

Wetsus - European centre of excellence for sustainable water technology Research Field Geosciences » Geology Geosciences » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 16 Oct 2026 - 15:00 (Europe/Amsterdam) Country Netherlands Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Mar 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2026.12 Is the Job related to staff position within a Research Infrastructure? No Offer Description Research challenges Although ecological evidence links weed communities to soil conditions, predictive plant-soil inference in agricultural fields remains limited. Weed distributions are highly dynamic, influenced by crop rotation, management history, disturbance, and plant-soil feedbacks, creating complex nonlinear patterns where species presence alone cannot explain soil variability. Key challenges include reliable weed detection in mixed canopies, separating soil signals from management effects, integrating multi-scale datasets, and accounting for microbiome interactions affecting weed and crop performance. In addition, optical plant traits must be translated into biologically meaningful indicators for robust modelling. Many existing AI approaches function as black boxes, limiting practical adoption. This project addresses these gaps by developing transparent AI frameworks that integrate species recognition, trait extraction, and soil sensing to predict soil properties while ecologically explaining disease risks and abiotic or biotic stress patterns. Your assignment You will develop an AI-enabled framework linking weed species composition and functional traits to soil properties and agroecosystem outcomes. The work includes extracting quantitative plant traits from spectral and imaging data, analysing soil physicochemical an...

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