Vacancy Delft University of Technology – PhD: Social Technologies for a Responsible Digital Future

Locatie Delft
Functietypes PhD positions
Wetenschappelijke discipline Engineering
Uren 38,0 uren per week
Salaris maximaal € 2717
Werk-/denkniveau University Graduate
Vacaturenummer ATTBM15-026
Vertalingen
About employer Delft University of Technology (TU Delft)
Short link www.academictransfer.com/30550

Description
The formation and growth of cities is generally explained by the concept of agglomeration economies: the range of performance-enhancing opportunities, amenities, infrastructure, skills and knowledge available to firms and people when they locate near to each other. This PhD project takes a step back from the mainstream of agglomeration literature. The project questions whether the agglomeration externalities known as ‘urbanisation economies’ are actually geographically linked to agglomerations. In other words, this project explores the geographical foundations of agglomeration theory. This could provide an explanation for why many small and medium-sized European cities, despite their assumed lack of agglomeration benefits, perform better than many large cities, which seem to enjoy more agglomeration benefits. ‘Borrowed size’ and ‘agglomeration shadows’ are important concepts in this research. The PhD student will study the spatial distribution of agglomeration benefits and costs, in the Netherlands and in (parts of) the U.S., using a wide range of proxies for these benefits and costs. This includes house prices, wages, productivity levels, crime, the occurrence of social problems and the presence of particular economic activities or urban functions. This leads to a fundamental questioning of the extent to which agglomeration benefits and costs can still be considered a phenomenon confined to agglomerations, and whether, and to what extent, they have transformed into regional externalities or network externalities.

Requirements
PhD candidates should elaborate frameworks, theories, models, and tools, such as innovative data science approaches and data collection, analysis and visualisation platforms. Advanced skills in programming and formal methods are required, as well as great affinity for social and global issues, excellent English language skills, social skills, and team spirit. The candidates should appreciate an international and highly interdisciplinary environment.

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