QUEEN ELIZABETH HOSPITAL BIRMINGHAM

QUEEN ELIZABETH HOSPITAL BIRMINGHAM

Summary of Skills, Experience and Qualifications
• Medical statistician, computer scientist or health informatician / Clinician with considerable expertise in statistical modelling.
• Skilled in data linkage and survival analysis methods.
• Experience in clinical or basic research in relation to cardiovascular and/or kidney disease, renal access or peripheral arterial disease is preferable.
• Applicants should have a PhD or at least 4 years research experience. Candidates with more than 10 years research experience will not be eligible for this position.
• The researcher would be a Marie Curie Fellow funded by a grant under the European FP7 programme. As a requirement of the grant this position is open only to researchers who have not been resident or having their main activity in the UK for more than 12 months in the last 3 years before recruitment.

Summary of Job Purpose & Principal Duties
A fixed term one year postdoctoral research fellowship is available in an international collaborative European project entitled ReDVA:
Development of hemodynamic solutions in Renal Dialysis Venous Access Failure (http://www.redva.eu). ReDVA is a joint research programme capitalising on the knowledge and expertise of the partners through exchanges of researchers and transfers of knowledge between research centres at the University of Dundee (project coordinator), Queen Elizabeth Hospital Birmingham, University of Limerick, and two companies Guerbet SA and the SME Vascular Flow Technologies Ltd. The aim of the project is to overcome the scientific and technical barriers to the understanding, development and adoption of technologies to combat the significant clinical problem of the failure of renal dialysis venous access.

The research for this fellowship will be undertaken at the Queen Elizabeth Hospital Birmingham (QEHB), United Kingdom. The successful applicant will be working within the informatics team at QEHB to extract data from established local databases and electronic patient records, and link these local data with records from the national Health Episode Statistics database. The linked dataset will be used to develop multistate models to predict survival of renal access. Data linkage and model development will be done in collaboration with the Health e-Research Centre (www.herc.ac.uk) in Manchester.
The project would give the fellow excellent links into a European network with an opportunity to develop further studies into a high volume, high importance clinical disease area for which a strong evidence-base is currently lacking.

For further information please contact Dr Nick Inston ( Nicholas.Inston2@uhb.nhs.uk ; Consultant surgeon, Renal Surgery and Transplantation, Queen Elizabeth Hospital Birmingham) or Dr Niels Peek ( niels.peek@manchester.ac.uk ; Reader in Health Informatics, Health e-Research Centre, University of Manchester).

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