WTO Internship Programme
World Trade Organization
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Full opportunity detailsNetherlands · On Site
International applicants, including Ugandan citizens, are explicitly accommodated, with Utrecht University providing support for Dutch visa and work-permit processing after selection. Candidates need an MSc or near-completed MSc in data science, statistics, applied mathematics, numerically oriented geosciences or a related quantitative field, together with strong machine-learning knowledge, large-dataset experience, Python or R skills and excellent English.
This doctoral project develops hybrid machine-learning approaches that integrate soil-process knowledge into modern artificial-intelligence methods for global soil mapping. Research may use neural networks, tabular transformers, Bayesian approaches and other GeoAI techniques.
Benefits
The appointment begins with one year and can extend to four years following a successful assessment. The published gross salary is EUR 3,059 to EUR 3,881 per month for full-time employment, plus 8% holiday pay, an 8.3% year-end bonus, pension, partially paid parental leave, flexible employment benefits and professional-development opportunities. Utrecht\'s International Service Desk assists selected international candidates with visa and work-permit processing.
Requirements
Applicants need relevant Master\'s-level quantitative training, machine-learning experience including neural networks or transformers, ability to handle large datasets, reproducible Python or R programming skills and interest in environmental or soil applications. The application requires a CV incorporating a motivation letter; selected holders of non-Dutch Master\'s qualifications must later provide Bachelor\'s and Master\'s diplomas and grade lists in English.
How to apply
Submit the CV and motivation letter through the Apply Now button on the Utrecht University vacancy page by 2026-09-06. Candidates selected for the process must provide requested academic documentation, with interviews scheduled for September 2026.