We are seeking a data scientist with an interest in infectious diseases to work on a project to develop tools to optimise global strategies to control the mosquito-transmitted disease dengue. They will join a 5-year Medical Research Council-funded project to improve estimates of the past, present and future global burden of dengue to guide high-level control decisions.

The post holder will be responsible for searching for existing datasets on dengue incidence and prevalence, building a new global open access database and designing custom visualisation tools. They will also contribute to developing mathematical and geospatial models that aim to make predictions for times and places where data are unavailable. This post will involve developing relationships with individuals at the World Health Organization and country Ministries of Health.

We are seeking a quantitatively minded person that prides themselves on attention to detail in data collection and curation and has a passion for data visualisation and improving the external reproducibility of epidemiological methods. Post holders should have a strong working knowledge of R (experience with package development and R Shiny desirable), experience with working with public health stakeholders and a working understanding of modern infectious disease modelling methods. Further particulars are included in the job description.

The post holder would join a growing group of modellers, epidemiologists and statisticians working across vector-borne diseases supervised by Associate Professor Oliver Brady.

This Research Fellow post is full time and available from 1 February 2022 until 31 January 2024 in the first instance, with the possibility for extension depending on project funding. The salary will be on the Academic scale Grade 6, in the range £40,611 - £46,119 per annum, inclusive of London Weighting). Non-UK applicants are encouraged to apply and funds are available to partially or wholly cover employment visa and health surcharge costs.

Applications should be made on-line via our website at http://jobs.lshtm.ac.uk. Applications should also include the names and email contacts of 2 referees who can be contacted immediately if shortlisted. Online applications will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process may be addressed to jobs@lshtm.ac.uk.