First listed on: 16 January 2023

CSIRO Postdoctoral Fellowship in Spatial Modelling for One Health

 

Acknowledgement of Country

CSIRO acknowledges the Traditional Owners of the land, sea and waters, of the area that we live and work on across Australia. We acknowledge their continuing connection to their culture and pay our respects to their Elders past and present. View our vision towards reconciliation

The Opportunity

  • Do you have a PhD in biostatistics, statistics, mathematics, epidemiology, engineering, physics, or a related discipline?
  • Keen to conduct innovative research leading to scientific achievements in the field of antimicrobial resistance (AMR)?
  • Join our high-performing research team at the Australian e-Health Research Centre (AEHRC) for this exciting postdoctoral role

CSIRO Early Research Career (CERC) Postdoctoral Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years of relevant postdoctoral work experience. These fellowships aim to develop the next generation of future leaders of the innovation system.

The CERC Fellow will conduct innovative research leading to scientific achievements in the field of antimicrobial resistance (AMR) in both spatial modelling and patient pathways through the healthcare system. They will play a key role in developing and implementing Bayesian spatio-temporal models to identify region and cohort specific risks as well as estimation of AMR associated mortalities and behaviours through the healthcare system. The CERC Fellow will apply statistical modelling on medical data to understand complex health and behavioural drivers of infections, as well as identify spatial and temporal associations across several Australian regions. Models and methods of interest include regression models in the frequentist and Bayesian frameworks. This position will involve developing and implementing statistical methods and software tools for analysing surveillance and other administrative datasets for public health and clinical applications. 

The position will form part of the high-performing research program at the Australian e-Health Research Centre (AEHRC - https://aehrc.csiro.au/) – a world class centre undertaking research and development across health and biomedical informatics and health services. The CERC fellow will have the opportunity to be part of a project that aims at closing the gap in health outcomes for the remote populations living in tropical Australia. They will be part of a project that demonstrates originality and innovation and introduces new approaches to a significant global and local problem of AMR in tropical Australia. 

Your duties will include:

  • Undertaking statistical modelling to assist with the development of spatiotemporal analysis of health and demographic data (related to AMR and other infectious diseases).
  • Deriving AMR resistance relative risk estimates while taking into account the spatial and temporal structure of the data.
  • Incorporating demographic and other socio-economic features at a regional level which may help identify factors associated with AMR resistance.
  • At a patient-level, using linked health data to determine patient flow and care pathways.
  • Utilising various analytic and statistical methodologies to evaluate, select, interpret, and validate large datasets (including linked health data).

Location: Herston (Brisbane), Queensland
Salary: AU$92k - AU$101k plus up to 15.4% superannuation
Tenure: Specified term of 3 years
Reference: 91009

To be considered you will need:

  • A doctorate (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as biostatistics, statistics, mathematics, epidemiology, engineering, physics, or a related discipline with comparable experience. Please note: To be eligible for this role you must have no more than 3 years (or full-time equivalent) of postdoctoral research experience.
  • Experience in application and implementation of statistical methods in the Bayesian framework.
  • Demonstrated proficiency with programming languages/packages, such as R and Python, including the ability to programme new analyses, clean and structure data, and develop and validate appropriate models.
  • Demonstrated experience in the selection of a wide range of statistical methodology for the development of workflows to address broad research questions. 
  • High level written and oral communication skills with the ability to represent the research team effectively internally and externally, including the presentation of research outcomes at national and international conferences.

For full details about this role please view the Position Description

Eligibility

Applications for this position are open to Australian/New Zealand Citizens, Australian Permanent Residents and Australian temporary residents currently residing in Australia. Appointment to this role is subject to provision of a national police check and may be subject to other security/medical/character requirements.

Flexible Working Arrangements

We work flexibly at CSIRO, offering a range of options for how, when and where you work. 

Diversity and Inclusion

We are working hard to recruit people representing the diversity across our society, and ensure that all our people feel supported to do their best work and feel empowered to let their ideas flourish. 

About CSIRO

At CSIRO Australia's national science agency, we solve the greatest challenges through innovative science and technology. We put the safety and wellbeing of our people above all else and earn trust everywhere because we only deal in facts. We collaborate widely and generously and deliver solutions with real impact. 

CSIRO is committed to values-based leadership to inspire performance and unlock the potential of our people.

Join us and start creating tomorrow today!

How to Apply

Please apply on-line and provide a cover letter and CV that best demonstrate your motivation and ability to meet the requirements of this role.

Applications Close

13 February 2023, 11:00pm AEDT




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