PhD in Engineering: Machine learning electroencephalograph predictors of central neuropathic pain in subacute spinal cord injury

The School of Engineering of the University of Glasgow is seeking a highly motivated graduate to undertake an exciting 4-year PhD project entitled ‘Machine learning electroencephalograph predictors of central neuropathic pain in subacute spinal cord injury’ within the Biomedical Engineering Division.

Central neuropathic pain (CNP) affects 7% of the general population and more than 50% of people with spinal cord injury (SCI). We propose to define how EEG markers of CNP evolve over time in SCI, starting before the onset of its physical symptoms. Early EEG markers will be used to identify the risk of each newly injured patient developing pain to recommend preventive treatment.

In this project we propose to validate the EEG classifier and to optimize its performance. The ultimate goal is to have a pain predictor based on a minimum number of EEG channels from key areas. In addition, a longitudinal study will reveal how spontaneous and evoked EEG markers evolve during the transition from subacute to chronic SCI CNP, improving our understanding of mechanisms.

The applicant will benefit from a multidisciplinary environment and collaborative research between the University and NHS and will be a part of world leading research community funded by International Spinal Research Trust.