/Department of Computer Science, University of Sheffield/
http://www.findaphd.com/search/ProjectDetails.aspx?PJID=35209&LID=1772
Applications are invited for a 3-year PhD studentship on statistical natural language processing. Deadline: 31 December 2011.
The aim of this studentship is to design machine learning methods to better capture information about the user from their social media activities and then use that information to summarise relevant new social media content. This research topic falls in the broader area of Natural Language Processing (NLP), where Sheffield University has established an internationally-leading reputation. In particular, through their widely-used GATE NLP toolkit (http://gate.ac.uk) which provides many indispensable tools for working with large unstructured text collections, including semantic search, information extraction and translation.
Candidates should have a First Class Honours or a good 2.1 degree in Computer Science or Mathematics and have excellent computer programming skills. Experience with machine learning techniques for natural language processing is essential, and detailed knowledge of text summarisation and/or user modelling would be highly desirable. Research experience with Facebook, Twitter, and other social media would also be desirable, but is not strictly necessary, as would be knowledge of GATE.
Funding Notes:
The grant will cover all study fees for EU and UK nationals only and a living stipend for three years. The stipend will provide £13290 p.a. for UK nationals or approximately £9000 p.a. for EU nationals.
References:
Dr Kalina Bontcheva's homepage http://www.dcs.shef.ac.uk/~kalina
Dr Trevor Cohn's homepage http://www.dcs.shef.ac.uk/~tcohn
NLP research group http://nlp.shef.ac.uk/
Machine Learning research group http://www.dcs.shef.ac.uk/ml -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 3505 bytes Desc: not available URL: <http://www.uib.no/mailman/public/corpora/attachments/20111103/a9fc4ba4/attachment.txt>