PhD in Computer Science Applied to Health EPSRC Industrial CASE Studentship 2014



Project: Predictive Algorithms for Telehealth Service Improvement and Evaluation

An interdisciplinary research project between the Health Technology, Innovation and Intervention research group (Faculty of Health and Social Care) and Intelligent Systems group (Computer Science – Faculty of Engineering and Science) at the University of Hull in collaboration with Philips Research UK (Cambridge).

Research Area: Health technology, predictive modelling.

PhD Supervisors: Dr. Kevin Goode (1st); Dr. Chandra Khambampati (2nd)

Industrial Supervisor: Dr. Steffen Pauws (Philips, Cambridge)

A PhD studentship for 3.5 years is available to work on the development of predictive algorithms to improve the efficacy of telehealth service delivery and evaluation in chronic disease management. Telehealth (or remote patient monitoring) is being introduced as a solution to meet the growing health management needs of patients with chronic disease. Such services are being deployed at increasing scale but the tools to evaluate their efficacy and cost-effectiveness in a timely manner are limited. This project will use clinical data sources related to heart failure and telehealth to explore the limitations of reporting clinical outcomes using conventional time-to-first-event methods. The project will include the identification, and/or development and comparison of novel end-point definitions (e.g. the win-ratio and patient journey), repeat event models (e.g. Poisson and longitudinal logistic regression) and cost-effectiveness analytical methods.

The successful applicant will receive a high level of training at the University and will be expected to gain a Masters or Diploma level certificate in Research Training in addition to their PhD. They will work closely with Philips Research (UK) based in Cambridge, where they will be expected to spend a minimum of 3-months.

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The student will receive a stipend of up to £17,776 per annum (tax free, subject to confirmation). Tuition fees will be paid by the University of Hull. Anticipated Start Date: 3rd February 2014 for 3.5 years.

The successful candidate must have a 1st class or 2i in a (bio)medical informatics, computer science or similar degree with excellent mathematical and programming skills, a strong interest in clinical predictive modelling, clinical epidemiology, biostatistics and some understanding of health economics (i.e. the cost-effectiveness of medical interventions). The applicant should be enthusiastic with excellent verbal and written communication skills.

Closing Date for Applications: Sunday 8th December 2013

Applicants should complete the University of Hull PhD application form http://tinyurl.com/c87umv8 and send it to Admissions Service (Postgraduate), University of Hull, Cottingham Rd, Hull, HU6 7RX, UK.

They should also send (i) a cover letter outlining your suitability for the study, what you hope to achieve from the PhD and your research experience to date; (ii) curriculum vitae; (iii) the contact details of 2 referees and (iv) a copy of the completed University of Hull PhD application form by email or by post to: Dr. Kevin M Goode, Faculty of Health & Social Care, Room 101, Aire Building, University of Hull, Cottingham Road, Hull HU6 7RX. Email: K.M.Goode@hull.ac.uk

Application open to permanent UK residents or EU nationals resident in the UK for 3-years prior to the start of the grant. Please check the EPSRC web-page for more details on student eligibility before you send your application http://www.epsrc.ac.uk/skills/students/help/Pages/eligibility.aspx

For informal enquiries, please contact Dr Kevin M Goode. E-mail: k.m.goode@hull.ac.uk; Tel: +44 (0)1482 464608 Skype: kevin.m.goode 

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To submit an application, please use the ‘Apply’ button below.

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