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:
Apply 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
Develop novel projects
- 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)
Informal enquiries can be made to: Chris.Clarkson@lstmed.ac.uk
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.
