Applications are invited for a 4-year PhD studentship at University of Exeter. The position is fully funded including fees and a generous stipend of £14.5k per annum. Details are available here:
The closing date for applications is 10th August 2017. Please share responsibly with interested individuals and mailing lists.
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The rise of the web and digital media has seen an explosion in the availability of big social data. This PhD project will apply natural language processing to large collections of text documents harvested from the web (e.g. social media, blogs, online news), in order to construct networks of interaction between people and organisations. These networks will then be analysed to explore how they change in response to external events, with the aim of developing methods to predict real-world events before they occur. For example, one application of such methods might be to derive a dynamic network of relationships between politicians based on online news articles – could this network be used to reveal patterns of power and influence, identify new political players, or to predict election outcomes?
The student will learn natural language processing and network analysis, with aspects of machine learning for identification of influential actors. The fully funded 4-year project is co-sponsored by University of Exeter and a fast-growing data science company with offices in London and Bristol. The studentship will be based in the Computer Science department at University of Exeter and will interact with a vibrant interdisciplinary data science research community centred on the new Data Science Institute. The project offers excellent prospects for training and career progression.
Candidates should have a strong background in a quantitative
discipline (e.g. maths, physics, computer science), with
programming skills and experience of data analysis.
Interested candidates are encouraged to contact Dr Hywel Williams ([log in to unmask]) for further information.
-- Dr Hywel T P Williams College of Engineering, Mathematics & Physical Sciences University of Exeter, UK Room: Laver 722 Phone: +44 1392 723777 Office hours: Tuesday 2-3pm_____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.