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  3. PhD student: Developing a model of geo-computational exposure assessment for studying health effects of urban environmental risk factors in Exposome-NL (1.0 FTE)

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PhD student: Developing a model of geo-computational exposure assessment for studying health effects of urban environmental risk factors in Exposome-NL (1.0 FTE)

We are looking for a colleague with a strong interest in environment and health.

ongeveer 2 maanden geleden


Domplein, Utrecht, Utrecht
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
36 - 40 uur
€ 2395 - € 3061 per maand


Would you like to uncover how our living environment is driving our health? Are you interested in geo-computational techniques? Then the gravity programme on the Exposome might be the research programme for you.
PhD project “Developing a model of geo-computational exposure assessment for studying health effects of urban environmental risk factors in Exposome-NL”. We are looking for an enthusiastic and creative Researcher to strengthen our research group. You will work in a multi-center study funded by the prestigious Gravitation programme of the Dutch research funding organization NWO. Exposome-NL is a 10-year research programme of multiple Dutch universities, coordinated by Prof Vermeulen (IRAS, Utrecht University). The environment we live in has a significant impact on our health, explaining an estimated 70% of the non-communicable chronic disease burden. A large number of environmental stressors may jointly affect our health. Leading scientists in Europe and the USA have formalized this perspective as the Exposome concept: the sum of all non-genetic drivers of health and diseases. Interacting with the genome, it defines individual health at different stages throughout the life course. Supported by recent developments in sensor technology, satellite observations, smartphone technology and data sciences, now is the time to move Exposome research from concept to practice. Exposome-NL will apply the Exposome concept to the Urban Setting, specifically the complex interplay between the built, social, physico-chemical, food, and lifestyle environment.

There is a need to scale up and generalize the different ways how the general external Exposome can be measured in terms of diverse (geo)data sources and (geo-)computational methods. Environmental factors have been modelled in different forms, including spatial fields (continuous value surfaces), spatial objects (discrete spatially bounded entities), events (spatially and temporally bounded entities) and networks (quantified relations between objects). In the past, approaches for different environmental stressors have been less systematic, ranging from simplistic point-in-polygon tests and buffer based approaches to network-based interaction measures on different computational platforms. The ambition of this project is to generalize computational models over different sorts of data, spatial information concepts (field, object, event and network) and computing infrastructures (desktop-based, database, cloud-based, and distributed). This includes developing semantic models of the different sorts of environmental factors, data sources and problem sizes, as well as semantic models of the different geo-computational transformations needed for assessing exposure. It also includes an investigation into scalable computational infrastructures (such as parallelization and cloud computing) and prototypical implementations for deploying exposure models for large problem sizes.

As a PhD student you will be responsible for developing the framework and tools to characterize the external Exposome in a systematic manner in close collaboration with other national partners. You will apply the framework to diverse environmental exposures such as air pollution, urban heat and urban green and compare with existing approaches. You will collaborate closely with PhD students within the Gravitation programme and international partners from a large European Exposome project also coordinated by Prof Vermeulen. You will publish the findings as papers in peer-reviewed scientific journals. These papers will form the basis of your PhD thesis.


We are looking for a colleague who has a completed Master's degree in computational geoscience, data science, GIScience, computer science, or a related discipline , with a strong interest in environment and health. We prefer colleagues with experience in conceptual modeling of geographic information and GIS workflows. This may include database design, ontologies of GIS models and workflow design. As our new colleague you should be a teammate, open for collaboration across scientific fields, and have the ambition to contribute to scientific progress as well as to perform societal relevant research. The candidate should be able to work independently and have good verbal and written communication skills in English. Furthermore, the candidate should have a solid background in programming and the development and deployment of computational services.


We offer a temporary position (1.0 FTE) for a period of one year. In case of a good performance an extension of 3 years is possible. The gross salary ranges between €2,395 in the first year and €3,061 (scale P according to the Collective Labour Agreement Dutch Universities) per month in the fourth year for a full-time employment. Salaries are supplemented with a holiday bonus of 8% and a year-end bonus of 8.3% per year. In addition, Utrecht University offers excellent secondary conditions, including an attractive retirement scheme, (partly paid) parental leave and flexible employment conditions (multiple choice model). More information about working at Utrecht University can be found here.

Additional information

For more information about this position, please contact:
Dr ir Gerard Hoek (Associate Professor ), via g.hoek@uu.nl.