Job description
Economic resources (e.g. wealth and income) are distributed unevenly among people and in space: within cities and between cities, people and resources are concentrated and segregated. Economic inequality and urban segregation are considered top priority challenges by the United Nations. Tackling them is urgent because economic inequality and urban segregation restrict the ability of the poorest individuals to get by in life, but they also affect life expectancy, social justice and cohesion for everyone.
One way to understand and address urban economic segregation is to model its dynamics, and to run and compare policy scenarios on how to reduce it. Following recent developments in analytical sociology and computational social sciences, generative modelling (such as Agent-based modelling) has proven valuable to implement, combine and test causal theories through mechanistic representation. By showing how urban economic segregation persists and evolves due to individual interactions in space, we aim to advance our understanding of the interplay between economic inequality and residential segregation and to better assess possible remediatory policies.
This doctoral position represents an exciting opportunity to combine and develop the latest methods of modular social simulation, empirically-calibrated agent-based models and spatially explicit population synthesis on a socially relevant topic. You will be expected to 1/Build a synthetic population from sociodemographic and spatial microdata ; 2/ Build a modular Agent-based model of urban economic segregation, that translates a set of identified theories into social mechanisms ; 3/Evaluate and calibrate the model configurations against sociodemographic and spatial microdata ; 4/ Implement, run and compare policy scenarios on the calibrated model ; 5/ Write, submit and present related articles to relevant journals and conferences.
This research programme should lead to two areas of innovation. First, you will advance research on urban economic segregation by providing a theoretically grounded and empirically calibrated agent based model on which to test policy scenarios. Second, you will participate in on-going methodological research on spatially explicit synthetic populations and modular model building (including reusable building blocks) in the field of social simulation. Please apply if you think these challenges are exciting opportunities for you to grow as a computational social scientist.
In order to meet the challenges of this doctoral project, you should have experience in the fields of spatially-explicit social simulation, model evaluation and population synthesis. social science and spatial sciences. The successful candidate will be funded by the ERC Starting Grant SEGUE and will work in close collaboration with its members: a PhD student, a postdoctoral researcher and the Principal Investigator Dr. Clémentine Cottineau. You will find support within the Urban Studies section of the Urbanism Department of the faculty of Architecture and the Built Environment – a recognised centre of expertise in working on urban inequality with longitudinal microdata –, and link up with the Multi-actor systems group at the TPM faculty of TU Delft.