The potential for using Natural Language Processing in the NHS Wales
Project ID: 21082
Annual Stipend: circa £11 k p.a.
Application Deadline: 3rd June 2018
Here is an exciting opportunity to develop and apply a technology that could significantly enhance the way some national health data is processed.
This is a funded MRes, including a generous stipend and tuition fees, with well-resourced circumstances for a successful scholarship.
The selected candidate will apply their technical and computational skills to develop an automated triaging system based on the Artificial Intelligence techniques associated with Natural Language Processing. This research opportunity, will allow the student to develop transferable knowledge and skills in this most exciting and active field of computational intelligence.
This Knowledge Economy Skills Scholarship (KESS) project will be held in the Faculty of Computing, Engineering and Science at the University of South Wales. KESS is a programme funded by the European Social Fund (ESF) awarded by the Welsh European Funding Office (WEFO) in the Welsh Government.
The project is backed by NHS Wales Informatics Service (NWIS).
Programme of research:
NWIS collect significant amounts of data that is recorded using natural language (as opposed to formalised and rigid structures). This natural language data is relatively easy to read and understand by humans with similar backgrounds to the author but is not easily interpreted and processed by a computer. Nonetheless, in recent years there has been a rapid growth in the use of Artificial Intelligence techniques that enable Natural Language Processing by computers. However, the extent to which the technology can be applied to NWIS data is yet unclear.
The MRes would enable the needed investigation into the potential and limitations of the Natural Language Processing techniques and approaches to be undertaken. The MRes will progress along three parallel and concurrent tracks:
- A mapping of NWIS data resources, with particular regard to those that contain natural language data and how they relate and interface with other resources. The envisaged outcome would be a clear and unambiguous inventory of what natural language data is collected, stored, and used.
- An analysis of the potential for using Natural Language Processing to improve the operational outcomes of NWIS. This part of the MRes would include an analysis of what has been achieved in similar and cognate organisations to NWIS, together with an appraisal of the various software solutions that have been deployed elsewhere.
- The development of a prototype demonstration that will show how Natural Language Processing paradigms and techniques could be gainfully employed within NWIS.
The studentship will cover the fees for a 1-year full-time MRes programme and pay a stipend of circa £11k p.a. There is also around £3k project support costs available for consumables, travel, minor equipment, training (including the KESS Grad School) and conference attendance.
The position is available from 1st October 2018.
Eligibility of Student:
To be eligible to hold a KESS studentship, you must:
- have a home address in the Convergence area (details below)* at the time of registration.
- have the right to take up paid work in the Convergence area* on completion of the scholarship.
- be classified by the University as ‘home’ or ‘EU’ for tuition fees purposes according to the University’s guidelines.
- satisfy University of South Wales’s admissions criteria: see below, qualifications and experience and application process
*The Convergence area covers West Wales and the Valleys, and is made up of the following 15 local authorities: Isle of Anglesey, Gwynedd, Conwy, Denbighshire, Ceredigion, Pembrokeshire, Carmarthenshire, Swansea, Neath Port Talbot, Bridgend, Rhondda Cynon Taf, Merthyr Tydfil, Caerphilly, Blaenau Gwent and Torfaen.
Qualifications and experience:
Eligible applicants will:
- Have a degree (2i or higher) in an appropriate computing or mathematics based subject
- Possess a reasonable understanding of artificial intelligence techniques
- Be highly self-motivated, with capacity to design and implement new computational algorithms
- Have well-developed and positively collaborative interpersonal skills
- Have an ability to deliver technical reports and communicate findings
To download an application package, please visit: Participant Application Package
For any queries on eligibility, please contact: KESS Team at Research and Innovation Services, University of South Wales: email@example.com Tel: 01443 482578
For informal enquiries or further programme information, please contact: Prof. Andrew Ware. (firstname.lastname@example.org).
Closing date for applications: midnight Sunday 3rd June 2018
(Interviews will be held w/c 11th June 2018).