Graduate Research Excellence Scholarship (GRES)

This PhD project at Monash University Malaysia aims to develop an AI-informed, community-grounded framework for understanding and mitigating antimicrobial resistance (AMR) risks within a planetary health context. The research builds on prior risk modelling and incorporates qualitative methods, including focus groups and interviews with communities in both high- and low-risk zones, to capture local knowledge, behaviours, and risk perceptions related to AMR. Additionally, key informant interviews with policymakers from the Ministry of Health, Department of Environment, and local councils will be conducted to map current policies, identify surveillance gaps, and explore opportunities for intervention.

Insights from these community and policy engagements will be integrated with outputs from advanced AI models, such as geospatial deep learning, graph neural networks, and explainable AI, to refine AMR risk maps and ensure their local relevance. The project is supervised by Professor Wong Kok Sheik and a multidisciplinary team of co-supervisors, including Dr Sicily Ting Fung Fung, Dr Patrick Tan Hock Siew, Dr Sara Subhan, Dr Qasim Ayub, and Dr Aswini L. Loganathan, all based in the Department of Engineering and Information Technology.

Successful applicants will be awarded the Graduate Research Excellence Scholarship (GRES), which provides a full tuition fee waiver and a monthly stipend for up to 3 years 6 months. To be eligible, candidates must hold a First Class Honours (H1) degree or its equivalence (H1E) recognised by Monash University Malaysia and meet the English language requirements. The research areas span bioinformatics, biotechnology, genomics, neuroscience, artificial intelligence, computer vision, data science, machine learning, biomedical engineering, and medical physics.

The application deadline is July 30, 2026. Prospective students are encouraged to contact the main supervisor with their academic background and achievements to determine suitability for the project. If deemed a good fit, applicants should submit their application via the provided link, ensuring the research topic matches the advertisement. Further details on application requirements and scholarship information are available through the university's submission guide and course application process resources.