Research Fellow in Simulation Modelling and Software Engineering
Work type: Fixed Term
Division/Faculty: Faculty of Medicine, Dentistry and Health Sciences
Department/School: Melbourne School of Population and Global Health
Salary: $73,669 - $99,964 (Level A)
Role & Superannuation rate: Academic - Full time - 9.5% super
About the role:
The successful candidate will be working in a team of epidemiologists, economists and computer scientists. You will take the lead role in the building and maintenance of our core simulation models, coded in Python. You will accordingly have a diverse set of tasks, from software engineering and coding, through to documentation of the same and training staff how to use the models.
The core Python code is part of code developed by the Institute of Health Metrics and Evaluation (home of the Global Burden of Disease), University of Washington. Accordingly, you will be intersecting with some of the world’s leading research in health metrics and software engineers that facilitate this.
The position is as an Academic Specialist – meaning you focus on the ‘engine room’ without an expectation to lead author papers and grants – although if this is a career direction you want, we can discuss this at interview. Regardless, you will be involved in many publications and outputs through your written summary of methods and delivery of results in tables and graphs.
The Population Interventions Unit is rapidly establishing itself as an influential research group and has been very involved in the State of Victoria’s COVID-19 policy response.
This is an exciting time, with huge potential to inform policy through simulation modelling at the intersection of epidemiology, economics and data science.
You will require an undergraduate or graduate degree in computer science, mathematics, engineering, statistics, or related field. Demonstrated experience in Python coding is essential, and experience in software engineering is highly desirable. Knowledge of the research fields and methods used in epidemiology and/or demography is desirable – and if you are not conversant with epidemiology and lifetables (in particular) you must have the curiosity and ability to quickly become proficient in those areas relevant to simulation modelling (like disease incidence and case fatality rates, burden of disease studies, costings). The ability to undertake statistical analyses of input data (e.g. regression modelling) is essential.
PhD in epidemiology (preferred), computer science, economics, demography or closely related discipline (e.g. biostatistics). You will need demonstrated skills and experience in using a statistical or programming code (Python desirable). Strong writing skills are essential. You will need good communication skills and the ability to work harmoniously and productively in a vibrant and multidisciplinary team.
Applications close: 30 Nov 2020 11:55 PM AUS Eastern Daylight Time