The project will explore how the dynamics of cities are reflected in and, therefore, can be sensed by mining online content. It will utilise an innovative data source of billions of archived web pages under the .uk domain during the period 1996-2013. It will exploit the unstructured textual data contained in these webpages in order to understand the changes that cities in the UK have undergone.
We are looking for a student with:
- Relevant social science background in either geography/planning/urban studies or linguistics. Alternatively, a computer science background and willingness to engage with the above disciplines.
- Strong computational background including experience in R or Python.
- Good statistical knowledge.
- Preferably, experience in Natural Language Processing and Machine Learning.
The Regional Science Association International (RSAI), founded in 1954, is an international community of scholars interested in the regional impacts of national or global processes of economic and social change.
Regional Science Association International
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.