PhD Study : Cognitive analytics for early diagnosis of protective immunity and severity of SARS-CoV-2 infection

Apply and key information  

Summary

​Background:

Surveillance of immunity to SARS-CoV-2 has been dominated by development of tests to detect antibody to key antigens expressed by the virus, especially spike glycoprotein. These tests invariably depend on research-lab based, high-tech methodologies such as ELISpot or flow cytometry. As a part of SOCA consortium [1] and COVRES-2 study, a NICSM based team has produced datasets to support: (a) analysis of the blood transcriptome and plasma proteome of mild and severe COVID-19 hospital cases (in order to develop diagnostic test for measuring protective immunity) and (b) decyphering the neutralising antibody profile of mild vs severe SARS-CoV-2 infected patients.

Datasets:

We [2] and others [3] have been actively working on Covid-19 research. We have established time series experiments on whole blood and PBMC samples (N=70) on N=10 hospitalised patients and have generated RNA-Seq data on them as a part of SOCA consortium study. We are also generating RNA-Seq data on mild (N=20) and severe (N=20) SARS-CoV-2 infected patients as a part of COVRES-2 study. We are also working towards generating Olink [4] proteomics data on N=120 individuals as a a part of COVRES-2 study.

Aim:

This PhD project will focus on:

  1. Identification of early transcription markers of immune response to SARS-CoV-2 which can be deployed for making a diagnostic test for measuring cell based protective immunity.
  2. Identification of transcriptomic and proteomic signatures in mild vs severe SARS-CoV-2 infected patients.
  3. Development of machine learning based models for predicting persistence of protective immunity and severity of SARS-CoV-2 infection.

Prospective candidate:

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.

This PhD project will provide opportunity to a PhD researcher to develop computational skills in RNA-Seq and protiomics data analaysis and machine learning.

For any informal enquiry and/or to discuss more about the project, please contact the supervisors: Dr Priyank Shukla (p.shukla@ulster.ac.uk), Dr David Gibson (d.gibson@ulster.ac.uk) ​

Ethical approval: Full ethical approval is in place to support this project.

Please note: Applications for more than one PhD studentships are welcome, however if you apply for more than one PhD project within Biomedical Sciences, 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
  • Clearly defined research proposal detailing background, research questions, aims and methodology

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.

  • Completion of Masters at a level equivalent to commendation or distinction at Ulster
  • Experience using research methods or other approaches relevant to the subject domain
  • Sound understanding of subject area as evidenced by a comprehensive research proposal
  • Work experience relevant to the proposed project
  • Publications record appropriate to career stage
  • Experience of presentation of research findings
  • A comprehensive and articulate personal statement
  • Relevant professional qualification and/or a Degree in a Health or Health related area

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

Recommended reading

  1. https://www.imperial.ac.uk/immunology-inflammation/research/covid-19-research/soca/
  2. Shukla  P, Pandey P, Prasad B, Robinson T, Purohit R, D’Cruz LG, Tambuwala MM, Mutreja  A, Harkin J, Rai TS, Murray EK, Gibson DS, Bjourson AJ. Immuno-informatics  analysis predicts B and T cell consensus epitopes for designing peptide  vaccine against SARS-CoV-2 with 99.82% global population coverage. Brief Bioinform.  (in press)
  3. Napolitano F, Xu X, Gao X. Impact of  computational approaches in the fight against COVID-19: an AI guided review of  17 000 studies. Brief Bioinform. 2021 Nov 11:bbab456.
  4. https://www.olink.com/

The Doctoral College at Ulster University

Key dates

Submission deadline
Monday 28 February 2022
12:00AM

Interview Date
April 2022

Preferred student start date
mid September 2022

Applying

Apply Online  

Contact supervisor

Dr Priyank Shukla

Other supervisors