Joint PhD Position in Urban Green Exposure & Health Analytics

Organisation/Company KU LEUVEN Research Field Environmental science » Ecology Researcher Profile First Stage Researcher (R1) Final date to receive applications 6 Mar 2026 - 23:59 (UTC) Country Belgium Type of Contract Temporary Job Status Full-time Offer Starting Date 1 May 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BAP
- Is the Job related to staff position within a Research Infrastructure? No

Urban green spaces are crucial for climate resilience, biodiversity and public health. Yet, most indicators used in planning and health research still reduce green to a simple percentage or NDVI value. They rarely capture how people actually see, access and experience greenery, nor how those experiences translate into concrete health outcomes.

The BRANCH project wants to change that. By combining conceptual work on green space typologies, advanced geospatial analytics, AI-based image analysis, citizen science and large‑scale health data, BRANCH will develop a new generation of human‑centred green exposure metrics and link them to health patterns in millions of people in Belgium.

To help build this framework, we are looking for a motivated PhD researcher who will work across KU Leuven and the University of Essex, at the interface of urban ecology, remote sensing, environmental epidemiology and data science.

This joint PhD will be carried out at both institutions, with the candidate dividing their time between Essex (2 years) and Leuven (2 years).

As a PhD researcher, you will play a central role in advancing BRANCH’s human‑centred understanding of urban green spaces and their health benefits. You will help develop a health‑oriented typology of urban green that brings together ecological characteristics, spatial configuration, and the way people actually see and access greenery in their daily environment. This requires synthesising insights from ecology, landscape architecture, environmental psychology and public health, and engaging closely with planners and health professionals to ensure real‑world relevance.

You will contribute to measuring green exposure from a human perspective, combining street‑level information, citizen‑generated data, and spatial analyses to assess how visible, accessible and equitably distributed different kinds of green spaces are.

A key part of your work will be to link these exposure metrics to large‑scale health datasets, exploring how different forms of green relate to mental and physical health outcomes across diverse population groups. You will collaborate with epidemiologists to help shape exposure variables, analytical frameworks and interpretation.

Throughout the project, you will also engage with stakeholders and citizen groups, contributing to co‑creation workshops, advisory boards and communication activities. Your work will help translate scientific insights into practical guidance for healthier, more equitable cities.

• MSc degree in Bioscience Engineering, Environmental Sciences, Geography, Public Health, Data Science, Remote Sensing, Geomatics or a closely related discipline
• Strong analytical and programming skills (e.g. Python or similar)
• Experience in at least two of the following areas: geospatial analysis / GIS; remote sensing or street‑level imagery; environmental exposure assessment; epidemiology or health data analysis
• Good written and oral communication skills in English
• Ability to work both independently and as part of an international, interdisciplinary team

• Experience with computer vision or deep learning (e.g. PyTorch, Tensor Flow)
• Familiarity with street view imagery or other street‑level/imaging datasets
• Background or interest in urban health, environmental epidemiology, or social determinants of health
• Affinity with citizen science, participatory mapping or stakeholder engagement
• Interest in translating scientific insights into policy and practice

• A 4‑year full‑time joint PhD fellowship, with a formal mid‑term evaluation after approximately 12 months
• Joint supervision by Prof. Ben Somers and Prof. Raf Aerts at KU Leuven,…