UNIVERSITY OF MANCHESTER

Research Associate in Health Data Science 

Location
Manchester, Greater Manchester (GB)
Salary
£31,604 to £38,833 per annum
Posted
18 Jun 2018
End of advertisement period
14 Jul 2018
Contract Type
Fixed Term
Hours
Full Time

Research Associate in Health Data Science 
Job Reference : BM&H-012186 

Location : Oxford Road, Manchester
Closing Date : 14/07/2018
Salary : £31,604 to £38,833 per annum
Employment Type : Fixed Term
Faculty / Organisational Unit : Biology, Medicine & Health
Division : - 
Hours Per week : Full Time
Contract Duration : Starting 1 August 2018 until 29 February 2020 

We are looking for a research associate to develop and apply methodology for clinical risk prediction in patients with one or more long term conditions. At present, clinical risk models take a cross sectional perspective on reality, incorporating only the most recently measured values from biomarkers and risk factors. This is often inadequate, as the long term conditions tend to move in and out of control, against a backdrop of slow deterioration. This can have implications for short term risks, e.g. of emergency hospital admission. The applicant will therefore develop dynamic risk prediction models, which update in real-time, and are able to predict risk of multiple outcomes simultaneously.

This is part of the EPSRC funded project “The Wearable Clinic: Connecting Health, Self and Care” which aims to create new personalized care plans for people with schizophrenia and chronic kidney disease. The researcher will work alongside a team developing algorithms to exploit information from wearable technology, which could also feed in to the prediction modelling. Also, the prediction modelling can feed back the need for interventions, which can be monitored through the wearable devices. The current role focuses on the wearable sensing aspects of the project, principally via algorithm development in Matlab (or similar) although part of the algorithm code will run on the wearable device, and so an awareness of computational complexity, code optimization, and working with embedded devices will be essential.

This position will suit applicants with the curiosity and intellect to develop new statistical learning approaches, yet with a firm handle on the rapid application to real-world problems. Expertise in statistics, health informatics and/or machine learning, in a health context, is therefore essential, as is exposure to large data sets, and the statistical programming skills to handle these.

If appointed at Research Associate level you must possess a PhD (or equivalent), or be close to achieving the degree, in Statistics, Heath Informatics, Data Science or a closely related field. Excellent oral and written communication skills will also be a requirement for the post.

The Division of Informatics, Imaging and Data Science is committed to promoting equality and diversity, including the Athena SWAN charter for promoting women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education. We particularly welcome applications from women for this post. Appointment will always be made on merit. For further information, please visit http://www.manchester.ac.uk/connect/jobs/equality-diversity/awards/athena-swan/.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies

Enquiries about the vacancy, shortlisting and interviews:

Email: matthew.sperrin@manchester.ac.uk

General enquiries:

Email: hrservices@manchester.ac.uk

Tel: 0161 275 4499

Technical support:

Email: universityofmanchester@helpmeapply.co.uk 

Tel: 0161 850 2004

This vacancy will close for applications at midnight on the closing date 

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