*Fully Funded EU PhD Studentship: Healthcare Data Analytics and Text Mining*
Closing date:

Apply as soon as possible
*Subject study:*

Health informatics, natural language processing, machine learning, text
analytics, public health, epidemiology
*Key Information:*

Healthcare systems have collected mountains of textual and numeric patient
records about disease activities, hospital admissions and visits, drug
prescriptions, physician notes and more. But medical research and related
industries like pharmaceutical industry are faced with enormous challenges
as a result of the very restrictive handling of such health data.

This PhD studentship offers an exciting opportunity of exploring and /or
developing machine learning, natural language processing and text analytics
techniques to extract valuable knowledge from SNOMED CT derived clinical
narratives. Such knowledge will enable better care, prognosis of patients,
promotion of clinical and research initiatives, fewer medical errors and
lower costs, and thus a better patient life.

The successful student will have the chance of working in a very dynamic
academic research environment offered by the world class UK Farr Institute
of Health Informatics Research (http://www.farrinstitute.org/). We make up
one part of this Institute – CIPHER (The Centre for Improvement in
Population Health through E-records Research):

You will be supervised by Professor Ronan Lyons
<http://www.swansea.ac.uk/staff/medicine/research/lyonsra/>, Dr Shang-Ming
Zhou <http://www.swansea.ac.uk/staff/medicine/learningandteaching/zhous/>
and Mr Phil Davies.

*The successful candidate is expected to start their PhD scholarship in
January 2017.*

For enquiry about the area of research, applicants are welcome to contact
Dr Shang-Ming Zhou regarding information by email or by telephone: (
s.z...@swansea.ac.uk/ +44 (0)1792 602580).

Applicants should have a minimum of a 2.1 undergraduate degree and/or a
Master's degree (or equivalent qualification) in Computer Science,
Computational Linguistics, Computing, Data science, Statistics,
Epidemiology, Health informatics, Medical Informatics, Bioinformatics, or
any other related areas.

This PhD scholarship is open to UK or EU applicants, or applicants with
indefinite leave to remain in the UK.
How to Apply

 To apply, please go to the website:

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