We are delighted to be partnering with King’s College London on this ESRC collaborative (CASE) PhD project funded through the London Interdisciplinary Social Science Doctoral Training Partnership (LISS DTP). The LISS DTP will award an Economic and Social Science Research Council (ESRC) PhD studentship for the project, covering tuition fees plus a stipend. The PhD student will also have opportunities to apply for additional funding for training, professional development and research activity.
The British Library manages EThOS, the national database of UK doctoral theses, which allows users to discover and access doctoral theses for their own research. The almost complete collection of metadata about more than 450,000 dissertations, however, also invites us to ask questions about the nature and production of knowledge in an institutional and geographic context across almost the entire UK. This anchors the project in classic social science questions about the impact of individuals, work and mobility on organisations and cultures.
Textual data of this scale is only interpretable and navigable through ‘distant reading’ approaches. Therefore, despite being rooted in the interests and concepts of the social sciences, the project will involve genuinely interdisciplinary work at the interfaces of both the natural sciences and the (digital) humanities. This research is therefore an exciting example of ‘computational social science’ (Lazer et al. 2009), as it involves the application of cutting-edge computational techniques to large, rich data sets of human behaviour.
For more details about the project and information on how to apply, please visit the LISS DTP website. The application deadline is 9 March 2018.
Candidates may apply for one of two studentship types: a 1+3 award (1 year Masters + 3 year PhD) or a +3 award (PhD only), subject to their existing academic/professional backgrounds. The project seeks to understand changes in the UK geography of academic knowledge production over time and across two or more disciplines. All applicants are therefore expected to demonstrate an interest in the underlying social science research questions and (at a minimum) basic competence in programming. Additionally, the successful applicant for the 1+3 route would be expected to complete King’s MSc Data Science programme, while the successful +3 applicant would be expected to demonstrate existing familiarity with core analytical approaches.