CSIRO Postdoctoral Fellowship in Mosquito Population Modelling

Date Posted: 20 Nov 2023

Location: Brisbane, QLD, AU Townsville, QLD, AU

Company: CSIRO

Acknowledgement of Country

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The Opportunity

  • Do you have a PhD in statistics, applied mathematics, machine learning, computer science, data science, or other related disciplines?
  • Exciting research opportunity in the development of innovative modelling approaches in the fight against mosquito species!
  • Join the CSIRO Health and Biosecurity team in collaboration with University of Queensland in this 3-year 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.


CSIRO’s Zoonotic and Arboviral Pathogen team, in collaboration with the University of Queensland are searching for a CERC Fellow to join the team to work on a number of next generation technologies to suppress or replace mosquito populations that vector disease, including the Wolbachia Incompatible Insect Technique, self limiting and gene-drive genetic engineering systems.  CSIRO and UQ are looking to expand our capabilities the optimal deployment of these population control technologies through the ongoing development of innovative modelling approaches to support adaptive decision making in the field.

As the CERC Fellow, your focus will be on extending and/or developing models that explore optimal population suppression and replacement strategies for deadly mosquito species such as Anopheles farauti, Aedes aegypti and Aedes albopictus in the Pacific region.  Your research would initially include analysis of data to understand how various environmental and other ecological factors contribute to variation in population distribution and abundance. Models that simulate suppression and replacement of mosquito populations might include predicting insect dispersal through urban landscape or exploring emerging delivery technologies such as drone releases.  Other outcomes may include defining trapping networks to monitor population size and predict optimal release strategies of mosquito control technologies.  Outcomes would improve delivery of each technology by reducing both cost and time to the desired outcome of optimal population suppression, replacement and a reduction of disease burden. The CERC Fellow is also expected to contribute more broadly to the overall research programme, based on their skills and interests.


Your duties will include:

  • Analysing data using statistical and/or machine learning approaches as appropriate to improve our understanding of population parameter variation based on available biological data.
  • Developing and/or extending mathematical and computational population process models to study the effects of different population suppression and replacement strategies across several spatial and temporal contexts.
  • Exploring novel hypotheses and provide recommendations for field trials of various next generation mosquito control technologies.
  • Delivering model outcomes to key partners after a period of 2 years.


Location: Brisbane or Townsville, QLD
Salary: AU$92,624 - AU$101,459 plus up to 15.4% superannuation
Tenure: Specified term of 3 years
Reference: 93263


To be considered you will need:

  • A doctorate (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as statistics, applied mathematics, machine learning, computer science, data science, or other related disciplines. Please note: To be eligible for this role you must have no more than 3 years (full-time equivalent) of postdoctoral research experience.
  • Data science skills, with experience in extracting and cleaning data from online sources, and using machine learning and other statistical approaches to explore causal relationships.
  • Mathematical modelling and computational simulation skills and experience in one or more of the following areas: stochastic processes, spatio-temporal statistical modelling, population modelling. This includes demonstrated scientific computing experience.
  • Bayesian inference skills for fitting models to data.
  • Experience working collaboratively in interdisciplinary groups.


For full details about this role please view the Position Description



Applications for this position are open to Australian/New Zealand Citizens, Australian Permanent Residents or you must either hold, or be able to obtain, a valid working visa for the duration of the specified term.

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

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How to Apply

Please apply on-line and provide a cover letter and CV.  Your cover letter should individually address the essential and desirable selection criteria outlined in the position description and outline your motivation in applying for this role.


Applications Close

2 January 2024, 11:00pm AEDT

11:00 PM

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