Research Fellow in Epidemic Analytics

**Job no**: 0061805
**Location**:Parkville
**Role type**:Full-time; Fixed-term for 2 years
**Faculty**:Faculty of Medicine, Dentistry and Health Sciences
**Department/School**:Melbourne School of Population and Global Health
**Salary**:Level A - $80,258 - $108,906 p.a. plus 17% super
Level B - $114,645 - $136,136 p.a. plus 17% super
- **Undertake an integrated program of research in the mathematical sciences to inform the design of infection disease surveillance systems**:

- **Work on a group project with staff from the School of Mathematics and Statistics (University of Melbourne), Curtin University, and Telethon Kids Institute**:

- **Salary packaging, subsidised health and wellbeing services, fitness and cultural clubs, Myki discounts, and a 25% discount on graduate courses to our staff and their immediate families**

**About the Role**
The Research Fellow in Epidemic Analytics and Surveillance System Design will undertake an integrated program of research in the mathematical sciences to study the design of infectious disease surveillance systems, with the aim of improving the public health utility of these systems. The appointee will be responsible for developing a simulation platform that couples mathematical models of disease transmission with models of surveillance (observation) processes. They will also develop a framework for evaluating the value of data generated by different surveillance system designs, drawing on methods from the field of information theory optimal design. Using the simulation platform and evaluation framework, the role of data from a range of surveillance methodologies (e.g., mass testing, sentinel GP surveillance, serological surveys, infection prevalence surveys, hospital-based surveillance) in generating evidence for public health decision-making (e.g., forecasting, intervention scenario modelling, estimating vaccine effectiveness) will be investigated. Completing novel surveillance approaches may be considered.

The project team complement each other’s skills, providing plenty of opportunities for growth and development. The research unit work with a hybrid model, splitting time between working from home and working from the office with an emphasis on flexibility around personal life.

Your responsibilities will include:

- Leading the development of a simulation platform that couples mathematical models of infectious disease transmission with models of public health surveillance (observation) processes.
- Establishing a framework for evaluating the information value of data generated by different surveillance methodologies.
- Reporting on research findings at regular meetings and through formal presentations at Centre, School, and Faculty seminars, national and international conferences, and partner organisations

**Who We Are Looking For**
You are an early career researcher with a PhD, preferably in Infectious Disease Modelling, with a strong understanding of statistics and modelling using computing software such as R, Python, MATLAB, or C/C++. You ideally have experience working with public health data and an understanding of how public health systems observe cases of disease and be able to develop models to represent these processes. Your strong interpersonal skills allow you to be an effective part of team, contributing to research and publications.

You will also have:

- Sound written and verbal communication skills, including the ability to communicate technical material to a range of less or non-technical stakeholders from both a research and policy environment.
- Ideally, experience in simulation modelling the transmission dynamics of infectious diseases, analysing data from infectious disease surveillance systems and working with health policy or other decision makers.

For further information regarding responsibilities and requirements, please refer to the attached PD.

**Your New Team - Infectious Disease Dynamics Unit, Centre for Epidemiology and Biostatistics**
The Infectious Disease Dynamics Unit at the Centre for Epidemiology and Biostatistics conducts research in mathematical epidemiology and Bayesian statistical methods for infectious disease analytics, infectious disease surveillance, decision-science and pandemic planning and response. The unit is a key node in the Parkville precinct-wide infectious disease modelling and analytics network. Staff and students work closely with colleagues in the School of Mathematics and Statistics, School of Computing and Information Systems and the Peter Doherty Institute for Infection and Immunity. The unit is led by Dr Freya Shearer, and supports 5 research staff based in the unit, and additional post-doctoral staff and graduate research students primarily based in the School of Mathematics and Statistics. The unit has a national leadership role in viral respiratory disease surveillance, influenza and COVID-19 forecasting and pandemic planning and response. It has led Australia’s national COVID-19 situational as