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  3. PhD candidate: Developing a framework for geo-computational exposure assessment models for urban environmental risk factors in Exposome-NL, a Dutch Exposome research programme (1.0 FTE)

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PhD candidate: Developing a framework for geo-computational exposure assessment models for urban environmental risk factors in Exposome-NL, a Dutch Exposome research programme (1.0 FTE)

Uncover how our living environment is driving our health.

ongeveer 2 maanden geleden


Domplein, Utrecht, Utrecht
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
36 - 40 uur
€ 2325 - € 2972 per maand


Would you like to uncover how our living environment is driving our health? Are you interested in geo-computational techniques? Then the Zwaartekracht programme on the Exposome, PhD project “Developing a framework for geo-computational exposure assessment models for urban environmental risk factors in Exposome-NL” might be the research programme for you.
We are looking for an enthusiastic and creative Researcher to strengthen our research group. You will be working in a multi-center study funded by the prestigious Zwaartekracht 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 various ways of measuring the general external Exposome 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 various sorts of environmental factors, data sources and problem sizes, as well as semantic models of the various 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 for the Netherlands in a systematic manner in close collaboration with other national partners. You will start by carefully studying existing approaches for the diverse environmental exposures. You will collaborate closely with several Phd students within the Gravitation programme and with 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 or computer science, or a related discipline with a strong interest in environment and health. 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 socially relevant research. The candidate should be able to work independently and have good verbal and written communication skills in English and preferably Dutch.


We offer a temporary position (1.0 FTE) for one year. In case of a good performance, extending the employment is one of the possibilities. The gross salary ranges between €2,325 in the first year and €2,972 in the fourth year (scale P according to the Collective Labour Agreement Dutch Universities) per month 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 Gerard Hoek (Associate Professor), via g.hoek@uu.nl. Please do not send your application to this address.