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Utrecht University

Postdoc in AI-driven Urban (Re)Design for Health at Utrecht University Utrecht University in Netherlands

Degree Level

Postdoc

Field of study

Computer Science

Funding

Paid postdoctoral position at 1.0 FTE for 12 months, extendable to 29.5 months after positive evaluation. Gross monthly salary is between €3,706 and €5,760 for full-time employment (salary scale 10 under the CAO NU), plus 8% holiday pay, 8.3% year-end bonus, pension scheme, partially paid parental leave, and flexible employment terms.

Deadline

Oct 15, 2026

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Country

Netherlands

University

Utrecht University

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Keywords

Computer Science
Environmental Science
Deep Learning
Geography
Artificial Intelligence
Urban Planning
Salud Pública
Human Geography
Urban Design
Salud
Human Mobility
ML

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About this position

Utrecht University is recruiting a Postdoc in AI-driven Urban (Re)Design for Health within the transdisciplinary ELEVATE project. The role sits in the Faculty of Geosciences, Department of Human Geography and Spatial Planning, and focuses on building an AI-enabled recommender system that turns scientific evidence into practical urban design guidance for healthier and more equitable cities.

The project combines artificial intelligence, geospatial data science, urban analytics, street-view imagery, GIS, smartphone mobility data, and qualitative insights. The successful candidate will develop and fine-tune foundational AI and machine learning models, design geographically context-sensitive recommendations that support active mobility such as walking and cycling, and improve model explainability, fairness, and robustness. The work also includes creating an interactive web interface, collaborating with municipalities, urban planners, designers, and residents, publishing scientific papers, presenting at conferences, and contributing to MSc supervision.

Eligibility highlights: a PhD in computer science, AI, data science, computational social science, urban analytics, geoinformatics, or a related field; experience with machine learning/deep learning and model fine-tuning; strong programming skills (Python, JavaScript, PostgreSQL); and strong academic communication and writing skills. Experience with geospatial or image-based data and an interest in urban health, mobility, public space, or sustainable cities are desirable.

Funding and terms: this is a salaried postdoctoral appointment at 1.0 FTE for 12 months, with the possibility of extension to 29.5 months after positive evaluation. Salary is €3,706–€5,760 gross per month for full-time work, plus holiday pay, year-end bonus, pension, and other employment benefits under the Dutch university collective agreement.

Deadline: 15 October 2026. Apply through the Utrecht University vacancy page and include a motivation letter, CV with code/paper links, two referees, and one representative publication or project example.

Funding details

Paid postdoctoral position at 1.0 FTE for 12 months, extendable to 29.5 months after positive evaluation. Gross monthly salary is between €3,706 and €5,760 for full-time employment (salary scale 10 under the CAO NU), plus 8% holiday pay, 8.3% year-end bonus, pension scheme, partially paid parental leave, and flexible employment terms.

What's required

A PhD in computer science, artificial intelligence, data science, computational social science, urban analytics, geoinformatics, or a related field is required. Applicants should have experience with foundational AI model development/fine-tuning and machine learning and/or deep learning, strong programming skills such as Python, JavaScript, and PostgreSQL with expertise in front-end and back-end development, and strong communication and academic writing skills. Preferred experience includes working with geospatial or image-based data, interest in urban health, mobility, public space, or sustainable cities, and the ability to work both independently and collaboratively in interdisciplinary teams.

How to apply

Apply via the 'apply now' button on the Utrecht University vacancy page. Submit a motivation letter (max. 2 pages), CV with links to published code and papers, contact details of two referees, and one representative publication or project example. Apply before 15 October 2026.

More information can be found here

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