"Research Associate in Computational Statistics"

Position Details

• Fixed Term until December 2026 | Part-Time at 0.4FTE
• Academic Level A | $86,423 - $104,734 p.a.
• Location: Bedford Park / Kaurna Country
• View Position Description

About the Role

The College of Science and Engineering is seeking a Research Associate in Computational Statistics to undertake research on the modelling and analysis of biofouling processes in marine environments.

This role will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how environmental factors and antifouling technologies influence biofilm development. The project is a collaboration between Flinders University, the Defence Science and Technology Group, the University of South Australia, Queensland University of Technology and Australian Naval Infrastructure, funded by Defence Innovation Partnerships.

The Research Associate will:

• Apply advanced statistical methods, including time series and Bayesian modelling, to analyse biofouling data and generate new insights.
• Lead and contribute to project planning, research design, and delivery of project milestones in collaboration with the research team and industry partners.
• Produce high-quality research outputs, including publications, grant applications, and conference presentations.

About You

You are a skilled and motivated researcher with expertise in computational and applied statistics. With a strong research track history, your well-developed technical and analytical skills will elevate the quality of research undertaken. You will be capable of working independently and in a team, as well as using your initiative to manage multiple projects and prioritise workloads.

As the successful candidate, you will also demonstrate:

• Completion of minimum 4 years of tertiary study and preferably a PhD (or significant progress towards a PhD) in Statistics or a related discipline, with expertise in applied/computational statistics.
• Proficiency in statistical programming languages such as R and Python, and experience with Bayesian modelling and time series analysis.
• A track record of research outputs, including publications or presentations at national or international conferences.

About the ARC Training Centre for Biofilm Research and Innovation:

Our centre aims to transform biofouling management strategies for maritime platforms by building on local and international expertise to mentor and train the next generation of interdisciplinary scientists and engineers. Anticipating evolving regulatory stringency, this project expects to establish a dynamic environment for industry partners, students and scientists to collaborate and develop biofilm management strategies. We are working with industries to develop innovative solutions that meet their needs and alleviate their biofilm related problems.

How to Apply and Information

You are required to submit Suitability Statement of no more than 3 pages, addressing the four Key Position Capabilities of the position description.

• Completion of minimum 4 years of tertiary study and preferably a PhD (or significant progress towards a PhD) in Statistics or a related discipline, with expertise in applied/computational statistics.
• Demonstrated ability using statistical programming languages such as R and Python, or equivalent.
• Ability to apply, adapt and/or develop analytical methods for the study of time series and Bayesian modelling.
• Demonstrated experience in statistical methodologies and applied/computational statistics.

For more information regarding this position, we strongly encourage you to contact Tamar Jamieson.