Thematic Cluster: Predict-and-Prevent Severe Dengue: AI-Guided Multi-Omics & Natural-Compound Screening
Join a high-impact research cluster focused on severe dengue, a major Southeast Asian health challenge. As a PhD student, you will integrate hospital-based clinical data with discovery science to identify early immune warning signals and translate them into diagnostic and therapeutic leads. You will gain expertise in single-cell immune profiling, next-generation sequencing, machine learning, and in silico screening of natural compounds. Supported by world-class facilities at the Monash Biomedicine Discovery Institute, you will work across immunology, virology, and data science. This program offers the opportunity to publish, develop deployable clinical tools, and contribute to regional health security.
Impact: The collective projects aim to deliver a validated early-risk panel for severe dengue, ready-to-use SOPs and code for implementation, concise policy or clinical briefs for Malaysian decision-makers, and a prioritized, ADMET-screened shortlist of natural compounds for preclinical testing.
Project 1 (Jeffrey Cheah School of Medicine & Health Sciences)
Precision blood-cell biomarkers for early prediction of severe dengue
We will establish a prospective dengue cohort at University Malaya Medical Centre (UMMC) to identify early blood-cell signatures predicting severe disease. Peripheral blood will be collected at first presentation; PBMCs and plasma will be processed and cryopreserved at JCSMHS/UMMC, with fresh-blood immunophenotyping (including neutrophils) performed in Kuala Lumpur. Cryopreserved samples will be sent to Melbourne for high-dimensional CyTOF and CITE-seq profiling. Data will be integrated using machine learning to develop a compact biomarker panel suitable for point-of-care diagnostics. Supported by LifeArc and a joint MUM–MUA clinical, immunology and bioinformatics team, this program delivers a validated predictive signature and industry-ready pipeline.
The ideal candidate will be recognized for prior experience in immunology and exposure to clinical or biobank-linked research, with competence in animal cell culture and core molecular biology techniques. Rigorous documentation, responsible data management, and clear scientific writing will be evidenced. Familiarity with basic analysis in R/Python will be preferred, and experience in omics-based data analysis will be considered an added advantage. Training and cross-site co-supervision with the Monash Biomedicine Discovery Institute (BDI) will be provided.
For enquiries, please contact Assoc. Professor Vinod Balasubramaniam
For more information about this project, please visit our GEMS website.
How to Apply
When you apply for admission into your preferred degree program you will be able to select your scholarship type. No separate application is required.
By clicking on a course, you will be directed to further information, including details on ‘How to Apply’.
However, before applying for a GEMS, it is recommended that you first contact the main supervisor for this GEMS research topic. Please provide details of your academic background and achievements to the supervisor so that they can assess your suitability for the GEMS research topic you are interested in.
Main Supervisor (Malaysia): Assoc. Professor Vinod Balasubramaniam
Associate Supervisor (Malaysia): Dr Premdass Ramdas
Associate Supervisor (Australia): Prof. Diana Hansen, Dr Stephanie Studniberg, Prof Wei Shi
Project 2 (Jeffrey Cheah School of Medicine & Health Sciences)
This Project is No Longer Available.
Project 3 (School of Pharmacy)
Molecular Dynamics (MD)/QSAR screening of natural compounds for dengue antivirals
We will develop a streamlined in-silico pipeline to prioritise natural anti-dengue compounds using molecular dynamics (MD) and QSAR modelling. Curated plant-derived and pharmacopeial libraries will be standardised, docked against dengue and host targets identified in Projects A-B, and evaluated via MD for complex stability (RMSD/RMSF, hydrogen bonds) and binding free energy (MM/GBSA). MD-derived features and chemical descriptors will train QSAR models using public antiviral datasets and small internal reference sets. Top candidates will be filtered by drug-likeness and predicted ADMET, delivering a ranked hit list and mini-panel for wet-lab validation. Outputs include curated libraries, reproducible code, QSAR models, and prioritised compounds.
The ideal candidate will be credited with laboratory experience in molecular virology, strong animal cell culture skills, and competency in standard molecular biology assays relevant to antiviral testing. Strength in hypothesis-led experimental design, meticulous record-keeping, and data integrity will be expected. Background in immunology and exposure to omics-based data analysis for target prioritization or mechanism studies will be considered advantageous. Structured training and cross-site mentoring will be provided, leveraging BDI platforms to advance shortlisted compounds toward validated leads.
For enquiries, please contact Dr Khaw Kooi Yeong
For more information about this project, please visit our GEMS website.
How to Apply
When you apply for admission into your preferred degree program you will be able to select your scholarship type. No separate application is required.
By clicking on a course, you will be directed to further information, including details on ‘How to Apply’.
However, before applying for a GEMS, it is recommended that you first contact the main supervisor for this GEMS research topic. Please provide details of your academic background and achievements to the supervisor so that they can assess your suitability for the GEMS research topic you are interested in.
Main Supervisor (Malaysia): Dr Khaw Kooi Yeong
Associate Supervisor (Malaysia): Assoc. Professor Vinod Balasubramaniam
Associate Supervisor (Australia): Prof. Diana Hansen, Prof Wei Shi
The above projects are open for application until positions are filled.