KU Leuven
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Joint PhD in Urban Green Exposure, Health Analytics, and Environmental Epidemiology KU Leuven in United Kingdom
Degree Level
PhD
Field of study
Data Science
Funding
The position offers a 4-year full-time joint PhD fellowship with a mid-term evaluation after approximately 12 months. The fellowship includes joint supervision and enrollment in a joint doctoral programme, with approximately 2 years spent at each institution. Specific stipend amounts and tuition coverage are not mentioned.
Deadline
Mar 6, 2026
Country
United Kingdom
University
KU Leuven

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About this position
This joint PhD position in Urban Green Exposure & Health Analytics is a collaboration between KU Leuven (Belgium) and the University of Essex (UK), focusing on the development of human-centred metrics for urban green exposure and their links to health outcomes at the population level. The project, part of the BRANCH initiative, addresses the limitations of traditional green space metrics by integrating ecological characteristics, spatial configuration, and human perception and access. The research will employ street-level imagery, citizen-generated data, GIS, and spatial analysis to measure green exposure and connect these metrics to large-scale health datasets.
The successful candidate will work under the joint supervision of Prof. Ben Somers and Prof. Raf Aerts at KU Leuven, and Dr. Ruoyu Wang at the University of Essex. The PhD programme is structured to spend approximately two years at each institution, providing a unique opportunity to bridge urban ecology, remote sensing, environmental epidemiology, and data science. The candidate will collaborate with epidemiologists, planners, and stakeholders, and contribute to co-creation workshops, advisory boards, and communication activities.
Applicants should have an MSc in a relevant field such as Bioscience Engineering, Environmental Sciences, Geography, Public Health, Data Science, Remote Sensing, or Geomatics. Required skills include strong analytical and programming abilities (Python or similar), and experience in at least two of the following: geospatial/GIS analysis, remote sensing/street-level imagery, environmental exposure assessment, or epidemiology/health data analysis. Excellent English communication skills are essential. Additional assets include experience with computer vision or deep learning (PyTorch, TensorFlow), familiarity with street view imagery datasets, and an interest in urban health, environmental epidemiology, citizen science, participatory mapping, or policy translation.
The position offers a 4-year full-time joint PhD fellowship with a mid-term evaluation after approximately 12 months. The fellowship includes joint supervision and enrollment in a joint doctoral programme, with approximately two years spent at each institution. Specific stipend amounts and tuition coverage are not detailed in the announcement. The expected start date is as soon as possible, but before May 2026. The application deadline is 06 March 2026. Applicants should apply via the KU Leuven online portal, submitting a motivation letter, CV, and contact details of two referees. Optionally, previous work such as thesis, reports, code repository, or publications can be included. For further information, contact Prof. dr. ir. Ben Somers at [email protected].
Funding details
The position offers a 4-year full-time joint PhD fellowship with a mid-term evaluation after approximately 12 months. The fellowship includes joint supervision and enrollment in a joint doctoral programme, with approximately 2 years spent at each institution. Specific stipend amounts and tuition coverage are not mentioned.
What's required
Applicants must hold an MSc in Bioscience Engineering, Environmental Sciences, Geography, Public Health, Data Science, Remote Sensing, Geomatics, or a closely related field. Strong analytical and programming skills (Python or similar) are required, as well as experience in at least two of the following: geospatial/GIS analysis, remote sensing/street-level imagery, environmental exposure assessment, or epidemiology/health data analysis. Excellent English communication skills are essential. Assets include experience with computer vision or deep learning (PyTorch, TensorFlow), familiarity with street view imagery datasets, and an interest in urban health, environmental epidemiology, citizen science, participatory mapping, or policy translation.
How to apply
Apply via the KU Leuven online portal. Submit a motivation letter, CV, and contact details of two referees. Optionally include previous work such as thesis, reports, code repository, or publications. Expected start is as soon as possible, but before May 2026.
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