Postdoctoral Research Associate; Computational Vaccine Discovery

Location:

Liverpool, UK

£40,704- £46,970 per annum salary range

Full-time, fixed-term contract for 12 months

Location:

Liverpool with hybrid working arrangement

Interdisciplinary malaria research programme at the Liverpool School of Tropical Medicine

Opportunities for career growth and learning and development

Requirement of a PhD in a relevant quantitative or life-science discipline

Need for strong programming skills, preferably in Python

Postdoctoral Research Associate (Computational Vaccine Discovery)
Salary: £40,704- £46,970 per annum

Contract:

Full time, Fixed term for 12 month

Location:

Liverpool (Hybrid, 3 days per week on site)

We are recruiting a curious, rigorous and delivery-minded scientist to help turn the complexity of vaccine design into a usable decision platform. Malaria remains one of the world’s most important infectious diseases, but the search space for new peptide-based vaccines is enormous. A single parasite proteome can generate millions of possible peptides, and the strongest candidates must satisfy multiple constraints simultaneously

You will join an interdisciplinary malaria research programme at the Liverpool School of Tropical Medicine and work within the Malaria GEN team, collaborating with international vaccine researchers and making use of large-scale computational resources. The initial focus will be T-cell antigen and peptide prioritisation, with opportunities to contribute to broader computational antigen discovery as the programme develops.

You will help shape the computational architecture, scientific methods and evidence model behind a platform designed to support real experimental decision-making. The role combines research with software and data engineering, alongside close collaboration with vaccine scientists. It offers the opportunity to build something ambitious yet practical at the intersection of malaria genomics, immunology, machine learning and translational vaccine research.

You can learn more about this opportunity by reading our blog post about the project, as well as exploring some of our previous work in this area.

In this role, you will have the opportunity to:

• Build the core decision platform at scale. Develop scalable, tested and documented local and cloud workflows for malaria peptide evaluation, MHC class I and II predictions, multi-omics integration, ranking and candidate-set optimisation across very large datasets.
• Integrate evidence and improve prediction. Combine antigen-presentation methods with HLA population coverage, parasite variation, conservation, expression, and other evidence layers while calibrating predictions with experimental data and quantifying model uncertainty and disagreement.
• Turn data and experiments into decisions. Develop transparent scoring, filtering and optimisation approaches that help collaborators compare candidates and design experimentally tractable peptide sets; ingest assay results, assess prediction performance and iteratively improve prioritisation methods.
• Collaborate and create reusable research outputs. Work with international collaborators to provide analyses, technical support and help with scientific interpretation, while producing reusable pipelines, structured datasets and databases, technical documentation, scientific reports, presentations and peer-reviewed publications.

The successful candidate will have:

• A PhD in a relevant quantitative or life-science discipline, or equivalent substantial experience delivering advanced computational research or data-science projects.
• Strong programming skills, preferably in Python, together with sound software-engineering practices.
• Experience analysing or managing large,…