PhD Psychology - Towards a novel biomarker for pain: advanced analysis of oscillatory brain activity in healthy and chronic pain individuals

Closing Date

7 May 2019

Salary

£15,009

Address

Department of Psychology and Department of Mathematical Sciences, University of Essex

Duration

3 years

The present proposal focuses on electroencephalography (EEG) oscillations as a brain biomarker of pain, both in healthy individuals and chronic-pain patients. This project is a step forward as it proposes to study whether EEG oscillations can:

• Predict the unpleasantness of prolonged pain in healthy individuals, and
• Predict ongoing pain in chronic patients.

The project’s impact stems from the combined use of psychophysiological and mathematical tools to study EEG data (ie advanced machine learning, brain network theory and connectivity analysis of healthy individuals and chronic-pain patients. The collaboration with Professor Bhaskar Dasgupta (Consultant lead of Rheumatology and Clinical Director of Research and Audit, Southend University Hospital NHS Foundation Trust in Essex) will provide us with data from a large pool of patients. 

What funding is available?

The award consists of a full Home/EU fee waiver, or equivalent fee discount for overseas students (see www1.essex.ac.uk/fees-and-funding/research for further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,009 per year in 2019-20), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel. This covers three years of study.

Find out more online. 

? www.essex.ac.uk/postgraduate-research-degrees/opportunities/towards-a-novel-biomarker-for-pain

Who are the supervisors?

The lead supervisor, Dr Valentini, is an expert in pain science and the study of brain activity by means of EEG, while Dr Antonopoulos is an expert in computational neuroscience and network inference. The co-supervisor will provide support and guide the student through the most advanced data processing aspects of the work. In combination, the supervisors will train the student in literature review, experiment design, data interpretation and EEG data collection, advanced machine learning and network inference. Further information about the project supervisors and their research interests can be found on the University website. 

Dr Elia Valentini – Lecturer in psychology and brain sciences, Department of Psychology.
? www.essex.ac.uk/people/valen80000/elia-valentini

Dr Chris Antonopoulos MIMA – Lecturer in applied mathematics, Department of Mathematical Sciences.
? www.essex.ac.uk/people/ANTON17606/chris-antonopoulos 

Am I eligible and how do I apply?

The successful candidate should possess:

• A Masters level degree with relevant experience in the analysis of multivariate psychological and physiological data
• Good skills in programming (particularly Matlab and Python) and advanced statistical analyses
• Strong motivation for the project and its basic and applied health-related aspects
• Excellent organisational and communication skills

Desirable criteria:

• Proficiency in the English language
• Knowledge of available EEG data analysis tools
• Experience on EEG source localisation and connectivity analyses 

Candidates will be asked to provide: 

• Transcripts 
• Covering letter and a detailed CV 
• Personal statement 
• One reference 

For more information and to apply, click here