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): 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 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: (email@example.com/ +44 (0)1792 602580).
Eligibility: 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: http://www.swansea.ac.uk/postgraduate/scholarships/research/health-informatics-kess-phd-healthcare-data-analytics.php