Identifying serum biomarkers in PFAS serum concentration using metabolomics

By October 6th, 2025

Project overview

Project title

Identifying serum biomarkers correlated with longitudinal and cross-sectional trends in PFAS serum concentration using metabolomics.

Project description

This project investigates the health impacts of PFAS exposure in firefighters using advanced metabolomic techniques to identify biomarkers. The expected outcome is the development of new biomarkers for PFAS exposure, enhancing health diagnostics and preventive measures. This research will potentially lead to improved health risk assessments, better regulatory policies, and enhanced safety for workers exposed to hazardous substances.

Supervisory team

University

Name of university supervisorJochen Mueller
Sandra Nilsson
Name of universityThe University of Queensland
Email addressj.mueller@uq.edu.au
s.nilsson@uq.edu.au
FacultyFaculty of Health, Medicine and Behavioural Sciences

CSIRO

Name of CSIRO supervisorDavid Beale
Georgia Sinclair
Email addressdavid.beale@csiro.au
georgia.sinclair@csiro.au
CSIRO Research UnitEnvironment

Industry

Name of industry supervisorCraig Barnes
Name of business/organisationAirservices Australia
Email addresscraig.barnes@airservicesaustralia.com

Further details

Primary location of studentCSIRO Dutton Park, 41 Boggo Road, Dutton Park QLD 4102, Australia
Industry engagement component locationAirservices Australia, 25 Constitution Avenue, Canberra ACT 2601, Australia

Airservices Australia, Airport Drive, Brisbane Airport QLD 4009, Australia

The University of Queensland, 20 Cornwall Street, Wollongabba QLD 4102, Australia
Other locationsThe University of Queensland, 20 Cornwall Street, Wollongabba QLD 4102, Australia
Ideal student skillsetA degree in biochemistry, cell biology, analytical biochemistry or equivalent is essential.

Experience with high-resolution mass spectrometry instruments, metabolomics or PFAS (Per- and polyfluoroalkyl substances), multivariate statistical analyses and artificial intelligence/machine learning (AI/ML) modelling techniques and exposure research is desirable but not a must as long as the student has a strong interest and willingness to learn.
Application close dateOpen until position filled
ApplyContact Jochen Mueller