Cognitive analytics of multiple long-term conditions in Northern Ireland

Summary

Multiple long-term conditions (MLTC) also referred as multimorbidity means when a person has more than one chronic disease [1]. Nineteen percent of the Northern Ireland’s (NI) population suffers from multimorbidity [2], with one in every five pregnant women is impacted by multimorbidity [3].

Multimorbidity has also emerged as a major global public health issue due to its associated adverse health outcome e.g., disability, poor quality of life, mortality, and increased health expenditure [4,5]. Older people (>40 years) are more likely to develop multimorbidity [1,4].

Shukla Lab at the Personalised Medicine Centre (PMC), School of Medicine, Ulster University, has developed Multi-Morbidity analysis Pipeline (MulMorPip) which discovered and characterised five multimorbidity endotypes (sub-types) in the UK Biobank [6].

UK Biobank is a rich repository of clinical and healthcare data of approx. 500,000 UK participants from England, Scotland, and Wales, but unfortunately none from NI. PMC’s internal database of NI participants (approx. 2,500) has data on multimorbidity.

The NI Cohort for the Longitudinal Study of Aging (NICOLA) study has recruited 8,478 people from across NI, providing a true representation of the population aged 50 and over [7].

The Health and Social Care NI Business Service Organisation Honest Broker Service provides researcher access to de-identified health datasets within a Trusted Research Environment.

Using these three datasets and deploying MulMorPip we will establish and characterise sub-types of multimorbidity across NI population.

We will then investigate disease trajectories in terms of their sequence and time of occurrence in each of these multimorbidity sub-types, which when revealed will help in developing personalised treatment pathways and early interventions to prevent further consequences of multimorbidity.

This PhD project builds on a Global Challenge Research Fund (GCRF) Networking grant awarded by the Academy of Medical Sciences UK in 2023 [8] and the UK Biobank study led by Dr Shukla [9].

Specific skills required of the applicant for this project:

The project will be entirely computational. Thus, we are seeking a student having a strong interest in computational approaches evidenced by good programming skills (preferable in Linux/Shell, Python and R) and knowledge in bioinformatics, machine learning, and statistics.

However, students from more biology-oriented background but strong interest to learn bioinformatics and programming are also encouraged to apply. Appropriate training will be provided during PhD study.

Important Information: Applications for more than one PhD studentship are welcome, however if you apply for more than one PhD project within Medicine, your first application on the system will be deemed your first-choice preference and further applications will be ordered based on the sequential time of submission. If you are successfully shortlisted, you will be interviewed only on your first-choice application and ranked accordingly. Those ranked highest will be offered a PhD studentship. In the situation where you are ranked highly and your first-choice project is already allocated to someone who was ranked higher than you, you may be offered your 2nd or 3rd choice project depending on the availability of this project.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Sound understanding of subject area as evidenced by a comprehensive research proposal detailing background, research questions, aims and methodology
• A comprehensive and articulate personal statement demonstrating interest in the subject area
• Research proposal of 1500 words detailing aims, objectives, milestones and methodology of the project
• Experience using research methods or other approaches relevant to the subject domain

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• Applicants should hold, or expect to hold a First Class Honours Degree in a relevant subject area
• Applicants should hold, or expect to hold a relevant Masters Degree at a level equivalent to commendation or distinction at Ulster
• Work experience relevant to the proposed project
• Track record of peer reviewed publications
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

PhD scholarships are available for this project to all applicants worldwide, regardless of residency or domicile, and will cover:

• Tuition fees.
• A maintenance allowance of approximately £22,000 (exact rate is to be confirmed) per annum for three years, subject to satisfactory academic performance.
• A Research Training Support Grant (RTSG) of approximately £900 per annum.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year, or part-time equivalent, funded from any source, including self-financing students, are NOT eligible to apply for an award.

Students in full-time employment are not eligible for an award.

Part-time PhD scholarships may be available at a 0.5 pro rata rate of the full-time scholarship, which would require a six-year registration period.

Due consideration should be given to financing your studies.

The University will award a successful candidate one of the following scholarships for the project, depending on the funding available at the time an admissions offer is made:

1. Department for the Economy (DfE) PhD Scholarships
2. Vice Chancellor’s Research Scholarships (VCRS)

Please note that the Terms and Conditions for scholarships are subject to change for 2027/28.