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Funded PhD Research Studentship, Natural Language Processing, University of Sheffield, UK

From: Leon Derczynski <leon@dcs.shef.ac.uk>
Date: Wed, 8 May 2013 11:23:53 +0200
Message-ID: <CAPjwwFqMGGBbUa+w+tUS-F1mM5BvLj9i71WbndG7Z=bXP6BGPg@mail.gmail.com>
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Apologies for cross-posting

Computing Veracity of Social Media Healthcare Content
University of Sheffield - Department of Computer Science

Natural Language Processing Group

3-year studentship

The NLP group at the University of Sheffield is inviting applications for a
fully funded PhD studentship on computing veracity of social media content.

Application closing date is 31 May 2013.

The aim of this studentship is to design natural language processing
methods to compute veracity of social media content and deal with the
specifics of medical language. The goal is to model, identify, and verify
healthcare-related misinformation and disinformation, as they spread across
online media (e.g. patient forums) and social networks. Natural language
processing (NLP) now provides many indispensable tools for working with
large unstructured text collections, allowing effective search, information
extraction and translation. Social media content poses a number of
difficult and interesting NLP research challenges. The studentship will
also involve a close collaboration with healthcare researchers from a large
NHS trust and opportunities for working with natural language processing of
clinical records.

The PhD studentship will be associated to a larger research project about
developing novel cross-disciplinary social semantic methods, combining
document semantics, a priori large-scale world knowledge (e.g. Linked Open
Data) and a posteriori knowledge and context from social networks, past
user behaviour, and spatio-temporal metadata. The research will also
involve use of and further development of GATE (http://gate.ac.uk), which
is a leading open-source NLP toolkit, developed by an established team of
12 researchers.

Candidates should have a First Class Honours or a good 2.1 degree in
Computer Science and have excellent computer programming skills. Experience
with natural language processing and machine learning techniques is
essential, and detailed knowledge of biomedical NLP, medical ontologies,
and Linked Open Data are 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 plus a travel fund for attending collaborative
meetings and international conferences.

For further information please contact Dr Kalina Bontcheva (

Leon R A Derczynski
Research Associate, NLP Group

Department of Computer Science
University of Sheffield
Regent Court, 211 Portobello
Sheffield S1 4DP, UK

+45 5157 4948
Received on Wednesday, 8 May 2013 09:24:25 UTC

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