We are pleased to invite UK, EU and international applications for a fully-funded PhD studentship in Computer-aided diagnosis for chronic lower back pain using machine learning from Teesside University’s Centre for Digital Innovation.
Chronic lower back pain (CLBP) is one of the major types of pain that affects many people around the world. It is estimated that 28.1% of US adults suffer from this illness and 2.5m of the UK population experience this type of pain every day. Most CLBP cases do not happen overnight and they usually develop from a less serious variant of acute lower back pain. Acute lower back pain can develop into a chronic one if the underlying cause is serious and left untreated. The longer a person is disabled by back pain, the less chance he or she returns to work and the more healthcare cost he or she will require. It is therefore important to identify the cause of back pains as early as possible in order to improve the chance of patient rehabilitation.
The speediness of early diagnosis can depend on many factors including referral time from a general practitioner to the hospital, waiting time for a specialist appointment, time for an MRI scan and time for the analysis result to come out. Currently diagnosing lower back pain is done by visual observation and analysis of the lumbar spine MRI images by radiologists and clinicians and not all clinicians who see these images could interpret them.
The project has a single aim which is to improve the efficiency of the diagnosis process of chronic lumbar back pain which is helpful for all health organisations specialising in spine and back pain diseases. The domain field expert Prof. Al-Jumeily will provide us with all the clinical support needed during the research.
The supervisor is Dr Ala Al Kafri from the School of Computing, Engineering & Digital Technologies.
The Fully Funded PhD Studentship covers tuition fees for the period of a full-time PhD Registration of up to four years and provide an annual tax-free stipend of £17,668 for three years, subject to satisfactory progress.
You should hold or expect to obtain a good honours degree (2:1 or above) in a relevant discipline. A master’s level qualification in a relevant discipline is desirable, but not essential, as well as a demonstrable understanding of the research area.
International applicants should have a standard of English at IELTS 6.5 minimum and will be subject to the standard entry criteria relating to ATAS clearance and, when relevant, UK visa requirements and procedures.
How to apply
Application is online.
- Closing date for applications is 5.00pm, 1 February 2023.
- Shortlisting and online interviews are expected to be held mid-March 2023.
- Successful applicants will be expected to start May or October 2023.