Post Doctoral Research Associate

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Reference:
MAR

Expiry date: 22:59, Tue, 7th Apr 2026

Location:

Liverpool

Full-Time, Fixed-term appointment for 18 months

Based in Liverpool with occasional international travel

The Liverpool School of Tropical Medicine (LSTM) is a world-leading centre for research and training in global health. The Vector Biology Department focuses on understanding the biology, ecology, and evolution of disease vectors to inform strategies for disease control.

We are seeking a Postdoctoral Research Associate (PDRA) to join the Malaria

GEN Vector Team on the Vector Observatory project () Malaria continues to pose a major global health challenge, and mosquito vectors are central to transmission. The project addresses three major hurdles in the use of genomic data in public health - access to big data sets, the technology to analyse these data, and the knowledge to interpret the results.

In this role, you will develop, optimise, and maintain cloud-native genomic surveillance tools, datasets,and training resources. You will apply these to study insecticide resistance and the population structure of malaria mosquito vectors, generating insights that directly support evidence-based malaria control strategies. This position offers a unique opportunity to work at the cutting edge of vector genomics, contributing to a global effort to improve malaria surveillance and control.

Given the multidisciplinary nature of the project we welcome applications from candidates who hold a PhD in a range of fields including computer science, bioinformatics, statistics, or genomics. Previous experience working with insect vectors is not essential and we would encourage all researchers interested in harnessing the power of genomics, and big data to address important public health issues.

Key responsibilities will include:

A
pply evolutionary genetic approaches to the study of disease vectors

• Design, develop, and implement genomic-based tools and methods to address fundamental evolutionary questions in Anopheles mosquitoes
• A key model for our work is on the evolution of insecticide resistance, but the PDRA would be encouraged to work on other related topics

Provide support and supervision to students and technical staff within the group

• Assist in the design and supervision of PhD student projects
• Support students and technicians working on similar topics, especially in the analysis of their data
• Generate ideas and data to support new project applications
• Contribute to the writing of research grants/fellowships in collaboration with PIs
• Disseminate findings through publications and conferences, as relevant to research

Ideally you will demonstrate:

• PhD in Computer Science, Bioinformatics, Statistics, or Genomics
• Experience or knowledge of next generation sequencing technologies, bioinformatics and statistical method development and/or epidemiology and large-scale data management
• Strong programming skills, ideally with experience in Python
• Well-developed research skills with the ability to present research findings in oral or written format
• Experience or knowledge of computational best practices
• Experience of training staff
• Evidence of preparing publications for specialist/ general science journals

(For a full list of essential and desirable criteria please refer to the job description and person specification)

• Generous occupational pension schemes
• Government backed “cycle to work” scheme.
• Affiliated, discounted staff membership to the University of Liverpool Sports Centre
• A range of additional family friendly policies

Application Process:To apply for the position please follow the apply link and upload your CV and covering letter.

Due to the volume of applications, we receive, we may close our vacancies early. It is therefore advisable to apply as early as possible if you would like to be considered for a role.

Inclusion is central to our values at LSTM.

We seek to attract and recruit people who reflect the diversity across our communities, regardless of sexual orientation, gender identity, ethnicity, nationality, faith or belief, social background, age and disability. LSTM…