Contract: Full time, FTC for 12 months
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 MalariaGEN 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 can learn more about this opportunity by reading ourblog postabout the project, as well as exploring some of our previous workin 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, complex biological, biomedical or similarly high-dimensional datasets.
- Experience with statistical analysis, machine learning, quantitative method development and model evaluation.
- Experience building reproducible workflows and analytical pipelines, ideally using HPC or cloud computing environments.
(For a full list of essential and desirable criteria please refer to the job description and person specification)
Application Process: To apply for this position please follow the apply link and upload your CV, complete our application form and attach a covering letter outlining your interest in the post, and how your skills and experience align.
Due to the volume of applications we receive, we may sometimes close our vacancies early. It is therefore advisable to apply as early as possible if you would like to be considered for a role.
Please click here to learn important information about applying for a position at LSTM.
Competitive
