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<p><font size="2">Dear colleagues,</font></p>
<p><strong><font size="2">We are hiring a PhD candidate at Utrecht University!</font></strong></p>
<p><font size="2">Are you interested in developing new <strong>machine learning methods for a challenging real-world application</strong>? This PhD project focuses on <strong>hybrid / process-informed machine learning for global soil mapping</strong>.</font></p>
<p><font size="2">The goal is to develop next-generation methods for geospatial prediction by integrating scientific process knowledge into modern AI approaches. The research will explore methods such as <strong>neural networks, tabular transformers, and Bayesian
approaches</strong>, with applications to large-scale spatiotemporal and environmental data.</font></p>
<p><font size="2">We are particularly interested in candidates with a strong quantitative background, for example in <strong>data science, machine learning, statistics, applied mathematics, computational geosciences, or related fields</strong>, who enjoy working
on interdisciplinary problems and have programming experience in Python, JS, and/or R.</font></p>
<p><font size="2">Interested? More information and application details can be found here:</font></p>
<p><a href="https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-position-develop-hybrid-machine-learning-for-global-soil-mapping"><font size="2">https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-position-develop-hybrid-machine-learning-for-global-soil-mapping</font></a></p>
<p><strong><font size="2">Application deadline: 6 September 2026.</font></strong></p>
<p><font size="2">For more information, please contact Madlene Nussbaum at <a href="mailto:m.nussbaum@uu.nl">m.nussbaum@uu.nl</a>.</font></p>
<p><font size="2">Please feel free to share this opportunity within your network.</font></p>
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<font size="2">With best regards,</font>
<div><font size="2">Angelos Chatzimparmpas</font></div>
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<div><font size="2">On behalf of Madlene Nussbaum</font></div>
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