PhD Research Studentship: Statistical Modelling of Natural Language
PhD Research Studentship: Statistical Modelling of Natural Language
Natural Language Processing and Machine Learning Research Groups
University of Sheffield – Department of Computer Science
3 year studentship
Applications are invited for a fully funded PhD studentship on statistical natural language processing. Application closing date is 16 April 2010.
The aim of this studentship is to design machine learning methods to better understand and utilise natural language texts. Natural language processing (NLP) now provides many indispensable tools for working with large unstructured text collections, allowing effective search, information extraction and translation. Language poses a number of difficult and interesting machine learning challenges. Statistical models can provide insight into the nature of language while also providing practical tools.
Possible topics include machine translation, grammar induction, parsing, language modelling and topic modelling.
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 and probabilistic modelling techniques is essential, and detailed knowledge of graphical models and Bayesian inference (MCMC, variational inference) would be highly desirable. A background in linguistics and/or fluency in multiple languages would also be desirable, but is not strictly necessary.
The grant will cover all study fees for EU and UK nationals and a living stipend for three years. The stipend will provide £13290 p.a. for UK nationals or approximately £8000 p.a. for EU nationals. The project will also provide travel funds for the student to attend international conferences.
For further information please contact Dr Trevor Cohn (tcohn@dcs.shef.ac.uk) or Karen Barker (k.barker@dcs.shef.ac.uk).
Applicants should apply using the online application form at:
Related links:
Dr Trevor Cohn’s homepage -
NLP research group - /
Machine Learning research group -
