3-year PhD opportunity at Keele University starting October 2017

Closing date - 28th July 2017
Interview date - 23rd August 2017

Applications are invited to work on an exciting 3 year PhD studentship in the Centre for Prognosis Research, based within the fields of cardiovascular medicine and statistics, which will benefit from expertise within two research institutes at Keele University. The Keele Cardiovascular Research group is based in the Institute for Applied Clinical Sciences (IACS) and has developed close links with the institute of Primary Care and Health Sciences (iPCHS) and the Centre for Prognosis Research. The multidisciplinary team has an established track record of original research using national electronic healthcare databases and state of the art statistical methodology to study optimal treatment strategies, risk stratification and outcomes in patients with cardiovascular diseases. The Institute for Primary Care and Health Sciences (iPCHS) is the largest and most successful Research Institute at Keele. 91% of Keele’s research in Primary Care has been judged world leading or internationally excellent by the Public Health, Health Services Research, and Primary Care assessment panel of the 2014 Universities UK Research Excellence Framework (REF).

We are looking to recruit a PhD student to work on the following project:

Project title:
Temporal trends and outcomes following acute myocardial infarction

Summary:
The aim of this funded PhD is to use large high quality electronic healthcare data to study temporal trends, clinical outcomes, multimorbidity and complications following acute myocardial infarction (AMI) using national in-hospital data derived from the United States and the UK. Though the project can be tailored to the student’s expertise and interests, the team are particularly keen for the student to consider some of the following objectives:

1.      To identify how comorbidities cluster (multimorbidity), whether particular clusters have greater impact on patient outcomes, and how such clusters change over time. Further work will investigate how these clusters of comorbidities differ across cardiovascular conditions.

2.      To describe temporal and regional trends in patient risk factors, as well as treatments and clinical outcomes following AMI. The student will develop statistical models to identify which risk factors have contributed importantly to observed temporal changes in patient outcomes following AMI. Further, the student will investigate heterogeneity in predictor-outcome associations across clusters of patients (e.g. regions, centres).

3.      To study temporal trends in complications following treatment of AMI, using statistical models to define how their nature has changed over time and to identify and predict the risk of patient subgroups sustaining such complications.

Methodology research will form an important part of the studentship, in terms of the development and evaluation of statistical methods for analysing big data for prognosis research. In particular, areas of interest within the group include prognostic modelling and issues in the development and validation of such models, the use of advanced survival methods, and evidence synthesis methods.

Alongside their PhD, the student will be encouraged to attend internal and external training courses; write and submit both applied and methodological journal articles; and attend and present at national and international conferences.

We are looking for a highly motivated person with a passion for statistics research, with a good first degree (2:1 or above) in a relevant discipline. A Masters degree in a statistical discipline is desirable. Funding is available for three years to cover fees for PhD registration (currently 2016/17 home/EU rates: £4,121pa) and a research studentship stipend of currently £14,057 per annum for 2016/17. Non-EU students would be required to pay the balance (currently approximately £8,000 per annum) of the overseas fees themselves.

For an informal discussion, please contact Statistical Supervisor Joie Ensor ([log in to unmask]), or Clinical Supervisor Professor Mamas Mamas ([log in to unmask]).

For further details, person specification and to apply please see here (Reference number: IACS2017/02): https://www.keele.ac.uk/pgresearch/studentships/

Thanks,
Joie

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