Research Fellow In Infectious Disease Modelling

As part of the broader national PREPARE programme, this research project will focus on the development of mathematical models to support future preparedness for epidemic threats in Singapore. We will develop pathogen-agnostic epidemiological models that share characteristics associated with the route of transmission focusing on two routes that are significant threats for Singapore – respiratory and mosquito borne transmission. The models will be used to identify national data needs to support epidemic response and to evaluate early containment options. By taking a systematic and documented approach to code development, we will ensure that the models can be rapidly adapted to account for emerging threats. The research project is a collaborative endeavour between Imperial Global Singapore (IGS) and the National University of Singapore (NUS). The position is based at the Imperial Global Singapore office located in the CREATE building on the NUS campus. The research fellow will join a vibrant cross-faculty interdisciplinary research environment currently hosting approximately 30 researchers working across 5 major programmes. The research fellow will also have a formal attachment to the Centre for Global Infectious Disease Analysis in the School of Public Health at Imperial College London. The mission of the Centre is to be an international resource and centre of excellence for research and training in the epidemiological analysis and modelling of infectious diseases. The Centre has built upon a world-leading research group in the Department of Infectious Disease Epidemiology at Imperial College London to undertake applied collaborative work with national and international agencies in support of policy planning and response across a wide range of emerging infectious disease threats and global health challenges. On a day-to-day basis, the research fellow will also work closely with their counterparts on this project at the Centre for Epidemic Research & Modelling (CERM) within the Saw Swee Sock School of Public Health at NUS. The mission of this Centre is to advance the science of infectious disease modelling, inform policies through innovative research, and train the next generation of modellers. Purpose of the Post The postholder will lead the development of a suite of pathogen-agnostic transmission models to capture the range of future potential threats from respiratory viruses. In doing so, they will work closely with other research staff on the project to extract key model features from the existing literature and to consider methods to capture these in a way that enables rapid adaptation of the model structures in the event of a new emerging virus. The postholder will use these frameworks to identify national data and gaps, and to evaluate response options for putative “disease X” outbreaks. Key Responsibilities Research Duties: • To work with the wider team to synthesise the literature on existing respiratory disease models • To develop mathematical models for respiratory virus transmission, and to use the models to explore response options • To work with researchers in the team and externally to define data needs and sources and to identify gaps in knowledge • To support capacity building including workshops with stakeholders in Singapore • To present findings via publications to referred journals and to colleagues at conferences • To attend relevant workshops and conferences as necessary • To develop contacts and research collaborations within the research and wider community in Singapore • To promote the reputation of Imperial Global Singapore Other Duties: • To undertake appropriate administration tasks • Contribute to departmental management as required • To attend relevant meetings nationally and internationally • To undertake any necessary training and/or development Person Specification Requirements Candidates/post holders will be expected to demonstrate the following: Essential (E)/ Desirable (D) Education PhD in infectious disease epidemiology, mathematical modelling, statistics or related subject or a similar quantitative discipline (E) Knowledge & Experience Experience in epidemiological data analysis for infectious diseases (E) Experience in infectious disease transmission dynamic modelling (E) Experience with reviewing, analysing and synthesising scientific papers and reports (D) Experience of working with external collaborators (D) Working with government officials, technical staff and policymakers…