Department for the Economy (DfE) funded PhD Studentship in Big Data Analytics for Early Diagnosis of Major Depressive Disorder

Supervisors
Prof Tony Bjourson
Dr Elaine Murray
Prof Sonya Coleman

Applications are invited for a Government funded PhD studentship tenable in the Faculty of Life and Health Science in collaboration with the Faculty of Computing and Engineering at the Magee Campus.

Project Summary:
In the UK, depression is predominantly diagnosed in primary care by general practitioners (GP’s), but diagnosis and treatment selection is largely subjective, and reliant on patient self-report and clinical judgment and experience. DSM-IV guidelines maintain that 5 out of 9 specific symptoms must be present for a minimum of two weeks, for a diagnosis of depression. Despite these standard guidelines, diagnosis and subsequent determination of episode severity is complex and variable. Based on DSM criteria there are over 200 possible ways to meet the criteria of symptoms of depression, and very little information to inform the best choice of treatment. Moderate to severe depression is predominantly treated with antidepressants, but this treatment is far from straightforward. Over 20 antidepressant medications are approved for clinical use and there is currently no empirical evidence to support treatment selection.
There are currently no validated biological markers for depression or response to treatment with antidepressant medications, but a number of candidate biomarkers have emerged. Development of a novel biomarker panel that could be integrated with clinical, physiological, behavioural, and environmental data to develop a decision tool which would allow clinicians to effectively diagnose and stratify patients with depression to determine the most appropriate medication for each individual would shorten the duration of untreated depression, help maintain compliance and ensure better treatment outcomes.
This project will focus on the development of big data autonomous learning, computational intelligence techniques for major depressive disorder, combining the expertise in intelligent systems of the ISRC and the mental health and stratified medicine expertise of NI Centre for Stratified Medicine.
Entrance Requirements:

Candidates should have ordinary UK residence to be eligible for both fees and maintenance. Non UK residents who hold ordinary EU residence may also apply but if successful will receive fees only All applicants should hold a first or upper second class honours degree in computer science, mathematics, electronics, neuroscience, computational neuroscience, medicine, veterinary medicine, computational biology or a cognate area, and be able to demonstrate strong cross-disciplinary interest. Applications will be considered on a competitive basis with regard to the candidate’s qualifications, skills experience and interests. Applications will be considered on a competitive basis with regard to the candidate’s qualifications, skills experience and interests. Successful candidates will enrol as of 1 January 2018, on a full-time programme of research studies leading to the award of the degree of Doctor of Philosophy.

The studentship will comprise fees together with an annual stipend of £14,553 and will be awarded for a period of up to three years subject to satisfactory progress.

If you wish to discuss your proposal or receive advice on this project please contact:-
Dr Elaine Murray ([Email Address Removed]), Professor Tony Bjourson ([Email Address Removed]) or Professor Sonya Coleman ([Email Address Removed]).

Interested parties can visit the web sites for Northern Ireland centre for Stratified Medicine: http://biomed.science.ulster.ac.uk/research-institute/stratified-medicine/Intelligent Systems Research Centre: http://isrc.ulster.ac.uk/

Procedure

For more information on applying go to ulster.ac.uk/research
Apply online ulster.ac.uk/applyonline

The closing date for receipt of completed applications is 1st December 2017

Interviews will be held in December 2017