PhD Opportunity at the National Centre for Antimicrobial Stewardship
Are you looking for a fully research-focused PhD opportunity in Clinical Data Science where you can apply machine learning to real-world healthcare challenges? This PhD vacancy with the National Centre for Antimicrobial Stewardship offers a unique chance to work on surgical antimicrobial stewardship and improve antibiotic use in clinical settings. Based in the Greater Melbourne Area, this role offers hands-on experience with electronic health records, predictive modelling, and advanced analytics while contributing to impactful healthcare research. If you are passionate about combining data science, healthcare, and research innovation, this PhD could be the perfect next step in your academic career.
About the Institution:
The National Centre for Antimicrobial Stewardship is a leading research body focused on combating antimicrobial resistance through innovative stewardship strategies. The program is hosted at the Peter Doherty Institute for Infection and Immunity in collaboration with the University of Melbourne. NCAS works across human, animal, and environmental health sectors, following a One Health approach to improve antibiotic usage and patient outcomes globally.
Key Responsibilities:
- Conduct original doctoral research using healthcare datasets such as electronic health records, pathology, and pharmacy data
- Develop and evaluate machine learning and deep learning models for surgical infections and antibiotic use
- Perform data extraction, cleaning, harmonisation, and analysis
- Build reproducible research software using Python and ML frameworks at the National Centre for Antimicrobial Stewardship
- Address challenges like missing data, bias, and class imbalance in clinical datasets
- Validate models for robustness, generalisability, and clinical relevance in this PhD Vacancy
- Publish research in peer-reviewed journals and present at conferences
- Collaborate with clinicians, data scientists, and multidisciplinary teams
- Participate in seminars, workshops, and academic activities
Educational Requirements for this Vacancy:
- Honours or Master’s degree in Biomedical Engineering, Health Informatics, Epidemiology, or related field
- Must meet PhD entry requirements at the University of Melbourne
Skills Required:
- Strong proficiency in Python for data analysis and machine learning
- Experience with healthcare or clinical datasets
- Knowledge of statistical modelling and machine learning techniques
- Familiarity with tools like Scikit-learn, PyTorch, or TensorFlow (preferred)
- Understanding of real-world data challenges (bias, missing data, noise)
- Strong research, analytical, and problem-solving skills
- Effective communication skills for technical and non-technical audiences
- Ability to work in collaborative, multidisciplinary environments
Benefits of the PhD Vacancy:
- Opportunity to work on high-impact antimicrobial resistance research
- Access to advanced healthcare datasets and digital health infrastructure
- Collaboration with leading researchers and clinicians
- Exposure to interdisciplinary One Health research
- Development of expertise in machine learning, clinical informatics, and digital health
- Strong academic career growth with publications and global exposure
- Work within a top-tier research environment in Australia
