PhD Study : Computational analyses of WGS and phenotypic data with treatment response from patients with multimorbid disease conditions

Summary

The concurrent occurrence of multiple chronic diseases in a single patient is known as multimorbidity and it is the most common chronic condition affecting more than 50% of people over the age of 65. Patients with multimorbidity have complex treatment needs that are not met by the single index disease-oriented approach. Thus there is an unmet need for better diagnostics and tailored therapies for patients with multimorbidity. Inflammation has been reported as a common occurrence in many patients exhibiting co-morbid or multimorbid diseases.

Within the Northern Ireland Centre for Stratified Medicine (NICSM) of Ulster University, located at Clinical Translational Research and Innovation Centre (C-TRIC) in the Altnagelvin Hospital site in Derry, we have recruited and consented 2500 patients for whole genome sequencing (total to be recruited 7000) with diseases that are related to inflammation (e.g. CVD, diabetes, RA, mental health etc.) and we are undertaking deep phenotyping and Whole Genome Sequencing (WGS) analyses of samples from these patients. Many patients from these cohorts have got multimorbid inflammatory disease conditions.

The main aim of the PhD project is to identify variants from the WGS data which can be associated with the responses of treatments which these patients are undergoing. Using recent Artificial Intelligence (AI) based algorithms, we aim to identify variants which can be predictive of patients’ treatment responses. We will deploy recent Deep Learning (DL) approaches, tailored for hi-dimension low-sample size (HDLS) data problems, for identifying variants from WGS and clinical profiles of patients for their further stratification.

Our hypothesis is that our Artificial Intelligence (AI) based approach will enable sub-classification of multimorbid patients based on analyes of their genomic, phenotypic and  treatment response data. We anticipate our computational study of big clinical datasets will contribute to improved patient outcomes. The use of AI algorithms that integrate clinical WGS data with patient health care records will facilitate development of software applications which can be deployed in clinical diagnostic laboratories, informing treatment strategies for potential early intervention, and drug efficacy, thus contributing to the optimal management of multimorbid conditions in patients.

This PhD project perfectly aligns with ongoing efforts of NICSM in biomarker discovery and development of analytical tools for patients’ stratification. 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 biomedical sciences, computational biology 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 the course of PhD study.

For any informal enquiry and/or to discuss more about the project, please contact the supervisors: Dr Priyank Shukla (p.shukla@ulster.ac.uk), and Professor Tony Bjourson (aj.bjourson@ulster.ac.uk).

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
• A comprehensive and articulate personal statement

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.

• First Class Honours (1st) Degree
• Completion of Masters at a level equivalent to commendation or distinction at Ulster
• Research project completion within taught Masters degree or MRES
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

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) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• 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) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living