Research Associate – Epidemiological Modelling
Employment Type: Full time (35 hour a week) or part-time considered (3 – 4 days/week)
Duration: Fixed Term contract until 30th June 2025 (possible extension)
Remuneration: $80K - $107K p.a. (+17% super and leave loading)
Work rights: Full working rights will be required for the duration of the contract
Location: Kensington Sydney, NSW
Who we are:
The School of Public Health (SPH) is internationally recognised as a leader in public health with research strengths across a range of health disciplines, including infectious diseases and immunisation, and global health. SPH has a core focus to investigate and provide new knowledge to help inform policy, governance, organisation, work, and leadership in the health sector through cross disciplinary research with both academia and industry. SPH also has strong associations with research centres and institutes throughout UNSW Medicine.
The Kirby Institute is a world-leading health research institute at UNSW Sydney. We work to eliminate infectious diseases, globally. Our specialisation is in developing health solutions for the most at-risk communities. Putting communities at the heart of our research, we develop tests, treatments, cures, and prevention strategies that have the greatest chance of success.
Why this role matters
This Research Associate will be responsible for conducting research to support two linked programs of research on COVID-19 modelling and epidemiology, working jointly across the School of Population Health and the Kirby Institute at UNSW. The Research Associate will focus on the mathematical modelling of longer term COVID-19 dynamics, using established mathematical and computational models of SARS-CoV-2 transmission. They will be responsible for updating models to incorporate new data and using these models as tools to investigate research questions relating to ongoing vaccination strategies and the potential impact of future variants of concern. This will involve developing familiarity with the COVID-19 literature and the underlying immunology, biostatistical analysis, and ODE and stochastic modelling.
Who you are:
- A PhD in infectious disease epidemiology, mathematics, physics, statistics, biostatistics, or other quantitative discipline, and/or relevant work experience. A PhD will be preferred.
- Demonstrated mathematics, statistics, and/or computer programming skills relevant to mathematical modelling, preferably with experience in mathematical modelling as relevant to infectious diseases, epidemiology, or immunology.
- Strong analytical and quantitative skills.
- Proven commitment to proactively keeping up to date with discipline knowledge and developments (such as the relevant COVID-19 literature).
- Demonstrated ability to undertake high quality academic research and conduct independent research with limited supervision.
- Demonstrated track record of publications in peer reviewed journals, and conference presentations, relative to opportunity.
- Demonstrated ability to work in a multidisciplinary team, collaborate within and across teams, and build effective relationships.
- Excellent written and communication skills.
How to apply:
Please click Apply now to submit your application online. Applications should not be sent to the contact listed below. Can you please provide a resume and a cover letter addressing your interest in the role. Please see the full position description found here.
Contact (job related questions only)
Dr Alexandra Hogan E: ***************@unsw.edu.au
Applications close: Monday, 10th October before 11.30pm.
UNSW is committed to evolving a culture that embraces equity and supports a diverse and inclusive community where everyone can participate fairly, in a safe and respectful environment. We welcome candidates from all backgrounds and encourage applications from people of diverse gender, sexual orientation, cultural and linguistic backgrounds, Aboriginal and Torres Strait Islander background, people with disability and those with caring and family responsibilities. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff.
The University reserves the right not to proceed with any appointment.