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Application deadline: 1 March 2021
In human geography and social science, the relation between different dimensions of the environment with individual health is an old but cogent research problem. Over the last decades this problem - in particular the relationship between the physical environment and mental/physical health - received more and more attention in large-scale empirical research as well as in policy contexts. Environmental factors typically addressed include land use patterns (green and blue areas, recreational and sports facilities, urban densities), transportation system (e.g., walking and cycling facilities) and local air quality and noise. Over the past years new options for studying the impact of environmental factors on health were brought forward. One is the strongly increased availability of (open) environmental and health data. Our research programme has access to a variety of these data, both in house stored and via the CBS data environment in the context of ODISSEI. In addition, new computational methods allow for processing and combining data and finding meaningful patterns and relationships in these data through the use of data science techniques such as AI.
The new Assistant Professor will investigate the impact of the urban environment on health, based on advanced data science and computational techniques, applied on environmental and health data. Since these relationships are investigated within the department’s Urban Futures research programme, the research will pay specific attention to the way in which the relationships between physical environment and health interact with social contexts and structures.
With regard to teaching, the Assistant Professor will play a key role in the renewal of the Bachelor's programme, as co-teacher in the first year Spatial Data and GIS course and in the transformation of our thesis project in year 3. In addition, s/he will teach courses in the Master's programmes of the department and supervise Bacherlor's as well as Master's theses.
Potential candidates have a strong background in data science and computational methods, including programming skills and working with big data. They can apply these techniques in the domain of physical environment and health, but they also have experience in analyzing the impact of the social context on health outcomes. In summary, the appointee will design an original research line on the impact of the urban physical and social environment on health, where integrative and interdisciplinary theoretical arguments are developed and tested with large-scale novel data and methods of analysis.
The ideal candidate has