This opportunity is now closed.

Funded PhD Opportunity

Personalized medicine using computational analysis of omics data and molecular interaction networks.

Subject: Biomedical Sciences


Summary

This project will use computational approaches to improve our ability to use big ‘omics’ datasets to understand differences between patient groups with respect to disease mechanism, disease progression, and drug-response. Stratified medicine (or personalized/precision medicine) depends on the identification of biological features that can be used to separate a patient population into sub-groups, to enable biomarker identification and therapeutic development. “Omics” methodologies such as whole genome or whole transcriptome sequencing, microarrays, and proteomics, are often employed to identify useful biological features, because their high-throughput nature enables the quantification of thousands of features in a single experiment.

One approach to stratification is to apply machine learning / artificial intelligence based algorithms to omics data generated from a large patient cohort in order to build a mathematical model that can correctly assign sub-group identity based on the most predictive biological features. However, this approach ignores another potentially important source of information: the network of known functional relationships between biological molecules. These may take many forms, including gene co-expression, protein-protein binding, miRNA-target and transcription factor to target interactions. Clustering analysis of functional association networks, in which the structural topology of the network is computationally analyzed to identify tightly interacting groups of molecules, has been successfully applied to diverse pathologies including cancer, cardiovascular disease, type 2 diabetes, asthma, and schizophrenia.

The central hypothesis of this project will be that our capacity to stratify a patient population based on high-throughput molecular data is improved by the inclusion of functional association data. At our disposal to test this are: omics datasets and functional association data from public repositories; and in-house datasets from several disease areas currently under study at the Northern Ireland Centre for Stratified Medicine (NICSM).

The candidate will develop computational method(s), which will involve: first to score network clusters based on the extent to which they are impacted at the molecular level in terms of genetic variants or differential expression, followed by deploying (training and testing) various machine learning algorithms to identify clusters whose scores are predictive of a patient’s disease sub-group. Success in the project will feed into the ongoing efforts of the NICSM in these disease areas, focused on biomarker discovery in the short term and therapeutic development in the longer term. In practical terms, the project is intended to develop, test, and implement an analytical pipeline to be built into the NICSM’s analytical platform.

The project will be entirely computational. Thus, we are seeking a student having a strong interest in computational approaches, evidenced by programming skills (such as in Linux/Shell, Python, and/or R), and preferably with knowledge in biomedical sciences, computational biology and/or statistics. However, students from a 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 PhD project, please contact the PhD supervisors: Dr William Duddy (w.duddy@ulster.ac.uk) and/or Dr Priyank Shukla (p.shukla@ulster.ac.uk).


Essential criteria

  • Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC)
  • 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

    Vice Chancellors Research Scholarships (VCRS)

    The scholarships will cover tuition fees and a maintenance award of £14,777 per annum for three years (subject to satisfactory academic performance). Applications are invited from UK, European Union and overseas students.

    DFE

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 14,777 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided).  For Non EU nationals the candidate must be "settled" in the UK.


Other information


The Doctoral College at Ulster University


Reviews

My experience has been great and the people that I have worked with have been amazing

Kieran O'Donnell - 3D printing of biological cells for tissue engineering applications

Watch Video  

Completing the MRes provided me with a lot of different skills, particularly in research methods and lab skills.

Michelle Clements Clements - MRes - Life and Health Sciences

Watch Video  

Throughout my PhD I’ve been provided with continuous support and guidance by my supervisors and the staff at the University.I’ve also received many opportunities to further enhance my professional development in the form of teaching experience and presenting my work at conferences which will aid in my pursuit of a career in academia or industry.

William Crowe


Key dates

Submission deadline
Monday 19 February 2018

Interview Date
6, 7 and 8 March 2018


Contact supervisor

Dr William Duddy


Other supervisors


Applying

Apply Online

Related Funded Opportunities in: Biomedical Sciences ,

The production of rhamnolipid biosurfactant by Pseudomonas aeruginosa growing in biofilms.

Closing date:
Sunday 1 September 2019
Subject:
Biomedical Sciences

 View Details

The regulation of rhamnolipid biosynthesis in Burkholderia thailandensis.

Closing date:
Sunday 1 September 2019
Subject:
Biomedical Sciences

 View Details

Diabetes

Subject:
Biomedical Sciences

 View Details

Genomic Medicine

Subject:
Biomedical Sciences

 View Details

Novel amphibian skin peptide-analogues for the treatment of type-2 diabetes

Closing date:
Wednesday 18 September 2019
Subject:
Biomedical Sciences

 View Details

Using the Eye to Predict risk for Cardiovascular disease- The Living Lab

Closing date:
Friday 27 September 2019
Subject:
Biomedical Sciences|Engineering

 View Details

The design and analysis of a novel photo-activated antimicrobial system

Closing date:
Sunday 1 September 2019
Subject:
Biomedical Sciences

 View Details

Stratified Medicine

Subject:
Biomedical Sciences

 View Details

Optometry and Vision Science

Subject:
Biomedical Sciences

 View Details

MRes in Biomedical Sciences

Subject:
Biomedical Sciences

 View Details

Molecular Pathology of Glaucoma

Closing date:
Wednesday 1 January 2020
Subject:
Biomedical Sciences

 View Details