LIVERPOOL JOHN MOORES UNIVERSITY

Research Assistant in Data Analysis

Location
Liverpool, United Kingdom
Salary
£27,511 - £32,816 per annum
Posted
Thursday, 26 September 2019
End of advertisement period
Monday, 21 October 2019
Ref
2777
Contract Type
Fixed Term
Hours
Full Time

Contract Type Fixed Term
Hours Full Time
Job Type Research
Salary £27,511 - £32,816 per annum
Vacancy Type Academic / Research Vacancies
Closing Date 27/10/2019
Documents 2777 RA Data Analysis.pdf

The Built Environment and Sustainable Technologies (BEST) Research Institute is looking to recruit a Research Assistant to work on a project in collaboration with Alder Hey Children’s Hospital, University of Liverpool and University of Oxford.

The Research Assistant will be responsible for undertaking the analysis of experimental data for the SHINE project, mainly in the form of acoustic signals for the detection of hip dysplasia in new born babies. SHINE project is funded by Arthritis Research UK as part of its commitment to preventing the onset of osteoarthritis. The project’s aim is to develop an acoustic device to identify developmental dysplasia of the hip in babies (DDH). DDH is a spectrum of disease. One per 1000 babies have a frankly dislocated hip, and 2-3% are diagnosed with some degree of hip dysplasia. DDH is associated with premature osteoarthritis and is the reason for 10% of all hip replacements, and is the most commonly identified cause of hip osteoarthritis in those under 60 years old. Early diagnosis is crucial to determine whether surgery is required in childhood, and to maximise adulthood outcomes. If DDH is identified early in infancy it can usually be rectified with a removable splint, worn for just a few weeks.

The position will also require you to assist with sensor development in addition to contributing to publications and dissemination of research outputs, including presentations at project meetings and related conferences.

You will be near to completion or hold a PhD in Data Analytics, Sensors, Computing or Engineering related subject ideally with knowledge of machine learning with excellent planning/project management and research skills.

Informal enquiries may be made to Dr Badr Abdullah, email: b.m.abdullah@ljmu.ac.uk

LJMU values diversity and provides a supportive and inclusive environment where everyone can fulfil their potential.

Please note all of our vacancies will be closed to applications at midnight on the advertised closing date, unless otherwise stated.