Health informatics, machine learning, text analytics, natural language processing, public health, epidemiology
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 facing 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, 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.
This project will involve industrial collaboration with the Clinithink Ltd. You will has the chance of working in a very dynamic academic research environments 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) http://www.swansea.ac.uk/medicine/research/ researchthemes/patientpopulationhealthandinformatics/ehealth-and- informatics-research/thefarrinstitutecipher/
You will be supervised by Professor Ronan Lyons, Dr Shang-Ming Zhou and Mr Phil Davies.
The successful candidate is expected to start the PhD scholarship in January 2018.
Scholarships are collaborative awards with external partners including SME’s and micro companies, as well as public and third sector organisations. The scholarship provides 3 years of funding with a 6 month period to complete the thesis. The achievement of a postgraduate skills development award, PSDA, is compulsory for each KESS II scholar and is based on a 60 credit award. Eligibility
This PhD Scholarship is offered for UK or EU applicants, or applicants with Indefinite Leave to Remain in the UK.
Applicants should have a minimum of a 2.1 undergraduate degree and/or a master's degree (or equivalent qualification) in the Computer science, Computational linguistics, Computing, Data science, Statistics, Epidemiology, Health informatics, Medical Informatics, Bioinformatics, or any areas related. Funding
The studentship covers the full cost of UK/EU tuition fees, plus a stipend. The bursary will be limited to a maximum of £14,198 p.a. dependent upon the applicant's financial circumstances as assessed in section C point 4 on the KESS II participant proposal form
There will also be additional funds available for research expenses.
*How to Apply*
Applicants are advised to contact Dr Shang-Ming Zhou regarding information on the area of research, by email or by telephone: (s.zhou at swansea.ac.uk / +44 (0)1792 602580).
Please go to the link below to submit the application: http://www.swansea.ac.uk/postgraduate/scholarships/ research/health-informatics-kess-phd-healthcare-data-analytics.php
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