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Détails de l’opportunité

PhD position: Develop Hybrid Machine Learning for Global Soil Mapping

Salaire
EUR 3,059 - 3,881 per month
Date limite de candidature
September 6, 2026
Durée du contrat
4 years
Type de contrat
Fixed-term / Temporary
Type de poste
Doctorat
Date de publication
July 17, 2026
Département
Department of Physical Geography
E-mail de contact
m.nussbaum@uu.nl
Domaine de recherche
Artificial intelligence
Résumé Explicify

Résumé de l'offre

Utrecht University is offering a 4‑year PhD in Hybrid Machine Learning for Global Soil Mapping. The project focuses on integrating process knowledge into AI models to produce more accurate, consistent global soil maps, addressing gaps in data‑scarce regions. Candidates should hold an MSc in data science, statistics, applied mathematics or a related field, with strong machine‑learning skills, experience handling large datasets, and programming in Python or R. The role is 1.0 FTE, 36‑40 h per week, with a gross monthly salary of €3,059–€3,881, holiday pay, year‑end bonus, pension, and flexible terms under the Dutch CAO NU. The PhD aims to culminate in a doctorate within the four‑year period.

Généré à partir du contenu enregistré de l'offre. Vérifiez toujours les détails dans l'annonce officielle.

Description du projet

Are you excited to develop cutting-edge AI methods that contribute to solving global environmental challenges? Join the Department of Physical Geography at Utrecht University as a PhD candidate and help shape the next generation of geospatial modelling.

Your job

Predicting ecosystem dynamics under global change requires accurate and consistent soil information at global scale. Current global soil maps are derived using empirical machine learning that often ignores known soil processes, resulting in inconsistencies across soil properties and underperformance in data-scarce regions.

This PhD project will develop next-generation machine learning methods for geospatial prediction by integrating process knowledge into modern AI tools. The research offers the opportunity to explore neural network architectures, tabular transformers or Bayes methods to include process-information into machine learning and to develop new geoAI approaches for spatiotemporal mapping usable across domains.

The project is embedded in the Computational Geography group at the Department of Physical Geography, where you will work with researchers in environmental geo-spatial AI method development, soil modelling and spatial statistics.

Your qualities

We look forward to your application if you have the following qualifications:

  • You hold a MSc (or near completion) in data science, statistics, applied mathematics, numerical oriented geosciences, or related field with strong quantitative focus;
  • Strong background in machine learning methods such as neural networks and transformers;
  • Knowledge on handling large scale datasets;
  • Programming skills in Python and/or R; familiar with reproducible coding and automated (geospatial) data analysis;
  • Familiarity or interest to dive into environmental or soil science applications and hybrid modelling (process-informed machine learning);
  • Strong interest in interdisciplinary scientific challenges at the interface of domain knowledge and data science and collaboration in a multidisciplinary team;
  • Excellent English oral and writing skills.

Our offer

  • a position (1.0 FTE) for 1 year, with an extension to a total of 4 years upon a successful assessment in the first year, and with the specific intent that it results in a doctorate within this period;
  • a working week of 36 - 40 hours and a gross monthly salary between € 3.059 and €3.881 in the case of full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
  • 8% holiday pay and 8.3% year-end bonus;
  • a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University also offers a range of its own schemes for employees. This includes arrangements for professional development, various types of leave, and options for sports and cultural activities. You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University.

About us

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Sharing science, shaping tomorrow.

Utrecht University’s Faculty of Geosciences studies the Earth: from the Earth’s core to its surface, including man’s spatial and material utilisation of the Earth – always with a focus on sustainability and innovation. With 3,400 students (BSc and MSc) and 720 staff, the faculty is a strong and challenging organisation. The Faculty of Geosciences is organised in four Departments: Earth Sciences, Human Geography & Spatial Planning, Physical Geography, and Sustainable Development.

The team of the Department of Physical Geography excels in research and education on BSc, MSc and PhD level. We research processes, patterns and dynamics of Earth’s systems from the mountains to the sea, and the interaction in between. This knowledge is essential for the sustainable management of our planet and to guarantee the availability of resources for the next generations. We have access to world-class laboratories like Geolab and Earth Simulation Lab, and to excellent high-performance computing facilities.

We are a lively department that hosts an active early career community (PhD-students, researchers and lecturers). We organize a warm welcome for every new member.

The department and its facilities are located at Utrecht Science Park. Utrecht is the fourth largest city in the Netherlands with a population of nearly 360,000 and forms a hub in the middle of the country. Its historical city centre and its modern central station can easily be reached from the Science Park by public transport or by a 15-minute bicycle ride. Utrecht boasts beautiful canals with extraordinary wharf cellars housing cafés and terraces by the water, as well as a broad variety of shops and boutiques.

More information

For more information, please contact Madlene Nussbaum via m.nussbaum@uu.nl.

Candidates for this vacancy will be recruited by Utrecht University.

Apply now

As Utrecht University, we want to be a home for everyone. We value staff with diverse backgrounds, perspectives and identities, including cultural, religious or ethnic background, gender, sexual orientation, disability or age. We strive to create a safe and inclusive environment in which everyone can flourish and contribute.

Knowledge security screening can be part of the selection procedures of academic staff. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology.

The interviews will take place on 17 and 18 September 2026. The first round of interviews may be held online via MS Teams. The preferred starting date is to be agreed upon mutually.

To apply, please send your curriculum vitae, including a letter of motivation, via the ‘apply now’ button.

Note that international candidates that need a visa/work permit for the Netherlands require at least four months processing time after selection and acceptance. This will be arranged with help of the International Service Desk (ISD) of our university. Finding appropriate housing in or near Utrecht is your own responsibility, but the ISD may be able to advise you therewith. In case of general questions about working and living in The Netherlands, please consult the Dutch Mobility Portal.

If you have an international (not-Dutch) Master-diploma you will be requested to send your BSc- and MSc-diplomas and gradelists (in English).


Contact académique

Department of Physical Geography m.nussbaum@uu.nl
Last Update Utrecht University uu.nl
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