MRes - Computational designing of peptide-based vaccine candidates for Lassa fever

Summary

Lassa fever (LF) is an acute viral illness caused by the Lassa virus and it appears in the World Health Organisation’s list of priority diseases for research and development in public health emergency contexts [1]. While about 80% of LF infected individuals have mild or no symptoms, the remaining 20% can experience severe disease affecting organs like the liver and kidneys, with a high risk of fatality, particularly in pregnant women. Human-to-human transmission can occur through contact with bodily fluids, especially in healthcare settings without proper infection control, putting healthcare workers at risk [2]. Currently, there is no approved vaccine for widespread human use, and treatment options for LF remain limited. The development of a LF vaccine is critical due to its substantial public health burden, particularly in West Africa, where it causes recurring outbreaks with high morbidity and mortality. Although a few vaccine candidates have entered early-stage clinical trials (phases 1 and 2), none have progressed to phase 3 or are near approval [3]. Progress is hindered by several challenges, including the virus’s genetic diversity [4]. Therefore developing a safe and effective vaccine would not only reduce the disease burden but also protect healthcare workers, curb outbreaks, and support global health security efforts [5].

The conventional ways of developing vaccine, which involves attenuated agents might take up 10-15 years of development. On the other hand, development of Machine Learning based Bioinformatics’ tools has made it possible to define vaccine candidates by in silico predictions [6]. Combining these Bioinformatics approaches, along with the advances in recombinant DNA technology, knowledge on the host immune response and the genetic background of the pathogen, vaccine development time can be reduced significantly. Shukla Lab at the Personalised Medicine Centre, School of Medicine, Ulster University, has designed peptide-based vaccine candidates for SARS-CoV-2 [7] and currently working on multiple viruses including LF.

Specific skills requirements of the applicant:  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 immunology, bioinformatics and statistics. However, students from more biology oriented background but strong interest to learn bioinformatics and programming are also encouraged to apply. This MRes project will provide opportunity to a researcher to develop computational skills in immunoinformatics and vaccine designing. Following [1-7] reading is recommended and for any further informal enquiry and/or to discuss more about the project, please contact the chair of the supervisory team: Dr Priyank Shukla (p.shukla@ulster.ac.uk).

Important Information: Applications for more than one MRes studentship are welcome, however if you apply for more than one MRes 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 MRes 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.

• Experience using research methods or other approaches relevant to the subject domain
• A comprehensive and articulate personal statement
• A demonstrable interest in the research area associated with the studentship

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
• Use of personal initiative as evidenced by record of work above that normally expected at career stage.
• Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.
• Relevant professional qualification and/or a Degree in a Health or Health related area

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 opportunity is open to UK/ROI applicants only.

MRes studentships will be available to top ranked candidates to cover tuition fees and a Research Training Support Grant of £900. All applicants will be considered automatically for an MRes studentship. Applicants who do not receive a studentship but meet admission requirements may be offered admission on a self-funded basis.

Applicants who already hold an MRes or a doctoral degree or who have been registered on a programme of research leading to the award of an MRes or doctoral degree are NOT eligible to apply for an award. Applicants who hold or who are registered on a taught Master’s degree are eligible to apply.