I no longer accept any more students.
Numerous PhD, MPhil and MSc students have enriched my research over the years, on topics varying from crosslingual study of text types using principal component analysis, to multidimensionality in concept representations, to automatic term extraction, to machine learning of template extraction rules, to design of onomasiological dictionaries and term banks, to improving software project management through ontology-driven text mining, to text simplification as assistive technology, to named entity recognition and opinion mining for Arabic, ...
The National Centre for Text Mining offers a rich text mining research environment. Academic staff there are primarily looking for research students interested in text mining topics, although would certainly welcome students interested in research in related areas of natural language processing.
They normally would expect research students to be computer literate and to be able to program, or at least to be at home with computational linguistic formalisms, natural language processing workflow frameworks, deep learning for natural language processing, etc., and, for PhD level study, to have previously studied some aspects of text mining or natural language processing.
If you are interested in being supervised by academic staff in NaCTeM for doctoral or MPhil research, please send them your research proposal. Please consult our information on how to apply for PhD or MPhil.
If you are interested in investigating text mining techniques, say, in relation to a specific application domain, such as biology, the social sciences, or the humanities, then do please contact them. We work very closely with colleagues in other domains, especially the three mentioned, and the text mining research environment here is very conducive to interdisciplinary and cross-disciplinary research.
Postgraduate taught MSc
The School of Computer Science has a number of taught MSc programmes in Advanced Computer Science. One of the major themes available within this programme is Making Sense of Complex Data, which includes a course unit on Text Mining.