Harnessing non-invasive genetics, AI detection and citizen science to monitor koala population dynamics, health and diet

Stipend: $40,000 per annum provided in fortnightly, tax free instalments, with an indexation to be applied in each year of candidature.
Project support: $3,000 per annum provided by RTP Allowance with additional industry project allowance available
RTP Fee-offset Scholarship: $36,000 per annum covered
Funding length: 3 years (with the potential for a 6 month extension upon application) 
Location: Fieldwork in the Brisbane City Council local government area and laboratory/project activities as required.

Project title: Harnessing non-invasive genetics, AI detection and citizen science to monitor koala population dynamics, health and diet 

The koala (Phascolarctos cinereus) is facing escalating threats across eastern Australia, particularly in rapidly urbanising landscapes where habitat loss, fragmentation, disease, vehicle strike, dog attack and climate stress continue to place pressure on remaining populations. Effective conservation management requires robust, scalable and repeatable approaches for detecting koalas, assessing population health, and monitoring change over time. 

This PhD project will develop and apply an integrated framework for koala monitoring in partnership with Brisbane City Council. The project will combine non-invasive genetic sampling, AI-assisted koala detection, disease screening, diet analysis, population genetic assessment and citizen science to support evidence-based koala conservation. 

The PhD will be structured around four major research aims: 

1. Develop a next-generation molecular toolbox for non-invasive koala genomic monitoring. 
   This will include optimisation and validation of DNA-based methods for individual identification, sexing, Koala Retrovirus subtyping, Chlamydia pecorum detection, dietary profiling and SNP-based analysis from koala scat samples. 
2. Design and evaluate an AI-assisted koala detection system. 
   This component will assess the use of real-time thermal and RGB detection technologies to assist koala surveys and improve the efficiency of locating fresh scats for genetic sampling. 
3. Assess contemporary koala population genetics, health and diet across Brisbane. 
   The student will undertake field sampling across Brisbane City Council’s local government area using a combination of citizen science, targeted field surveys and AI-assisted detection. Genetic and health data will be used to assess population structure, genetic diversity, disease patterns, diet and spatial patterns relevant to conservation management. 
4. Compare contemporary results with previous koala population data. 
   The project will build on previous Brisbane koala genetic datasets from 2016–2021 to assess temporal changes in population structure, connectivity, genetic diversity, pathogen patterns and diet.  

The project will deliver a thesis by publication, with chapters designed as peer-reviewed scientific manuscripts. The research will also generate applied outcomes to support Brisbane City Council’s koala conservation planning, monitoring and management. 

Industry Partner and Student Host: Brisbane City Council 

Scholarship applicants must be eligible to undertake a PhD. Verify you can meet eligibility requirements outlined on the Graduate Research School website. If you are applying for ‘Honours equivalence,’ please ensure that you provide detailed information to support your case. 

Applicants should have a strong background in one or more of the following areas: 

• conservation genetics, molecular ecology, genomics or wildlife biology

• ecological fieldwork and/or wildlife monitoring  

• bioinformatics, population genetics or spatial analysis  

• non-invasive DNA sampling, preferably using wildlife scats  

• koala ecology, disease, conservation management or urban wildlife conservation  

• citizen science and community-based conservation programs.  

Applicants with experience in molecular laboratory methods, genetic data analysis, wildlife field surveys, or applied conservation research will be highly regarded. 

Applications will be accepted from Australian residents and permanent residents. 

Applicants should contact Associate Professor Fiona Hogan prior to submitting an application.  

Application closing date: 19 June 2026, 11:59 pm

How to apply: Applicants must submit their application with all necessary documents by completing the HDR Candidature application 

Commencement date: TBC July 2026