PhD Scholarship at Monash University
Do cutting-edge research at the intersection of cryo‑EM, genome-wide profiling, and AI-driven modelling.
Work with world‑class cryo-EM/cryo-ET imaging and AI tools to discover how the dangerous bacterium Klebsiella pneumoniae adapts its outer shell to survive - foundational knowledge on cell signalling and gene regulation that will help drive new strategies to combat this major antibiotic‑resistant threat.
Scholarship opportunity:
- Fully-funded, priority level scholarship
- PhD: 3 years
- Hosted at the Monash Biomedicine Discovery Institute in collaboration with the ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS).
About the Project
This project will use cutting-edge cryo-electron microscopy at the Ramaciotti Centre for Cryo-Electron Microscopy to determine the first full-length structure of a membrane-spanning two-component sensor kinase from the important human pathogen Klebsiella pneumoniae. By combining structural biology with genome-wide profiling and state of the art AI modeling, the candidate will map the signalling networks governing bacterial outer membrane permeability, addressing a fundamental question in cell biology.
- Contact: Dr Thomas McClean or Professor Trevor Lithgow
PhD Scholarships at the Australian National University (ANU)
Do cutting-edge research at the frontiers of AI-driven Whole-Cell Modelling!
We invite applications for two fully funded, 3.5-year PhD positions based at the ARC Centre of Excellence in Mathematical Analysis of Cellular Systems (MACSYS) Node at The Australian National University (ANU).
2026 PhD applications are open for April (international & domestic), August (international) and October (domestic) rounds.
Interested candidates please contact supervisor(s) with the following documents:
- Cover Letter (which can be in an email format), outlining your background and interested research areas
- CV
- Academic transcripts
Project 1
We are interested in these research areas: (1) Hybrid Whole-Cell Modelling: Combine mechanistic cell models with modern ML to deliver robust, well-calibrated predictions across conditions and perturbations. (2) Agentic AI Virtual Cell: Integrate molecular foundation models with single-cell multi-omics data and use agentic/active learning to propose the next best perturbations to improve generalisation. (3) Genomic & RNA Foundation Models: Train genome/RNA foundation models that translate sequence and regulation to function and phenotype, enabling principled in silico perturbations and design. (4) Multi-omics Modelling: Fuse transcriptomics, proteomics, metabolomics and perturbation data to infer cell states and dynamics that power whole-cell model construction.
Students with backgrounds in computer science, mathematics, or computational biology and strong ML/mathematical modelling skills are encouraged to apply.
Supervisor contact: Associate Professor Jiayu (Jean) Wen (Jiayu.wen@anu.edu.au)
Project 2
AI-Driven Decoding and Design of RNA-interacting molecules. This PhD project will develop integrated AI systems for biomedicine to decode and engineer molecules that specifically target RNA, a key challenge for cell biology, biotechnology, and RNA-targeting therapeutics. It aims to explore the combination of RNA-aware deep learning models, diffusion-based molecular generation, and agentic reasoning to design synthetic RNA-interacting molecules. The research leverages multimodal training on sequences, structures, and interaction data (including RNA chemical modifications), incorporates domain-specific biological constraints, and explores agentic AI to build hypothesis-driven workflows that bridge interaction prediction, rational molecular design, and experimental validation, thereby accelerating the development of programmable RNA-targeting tools.
Supervisor contact: Professor Eduardo Eyras (Eduardo.eyras@anu.edu.au)
PhD Scholarships at The University of Melbourne
Do cutting-edge research at the frontiers of Computational & Mathematical Biology
We invite applications for four fully funded PhD positions based at the School of Mathematics and Statistics, Faculty of Science, The University of Melbourne, and the ARC Centre of Excellence in Mathematical Analysis of Cellular Systems (MACSYS).
These positions offer an exciting opportunity to work at the forefront of computational and mathematical biology on projects such as:
- development of interoperable virtual cell modules simulating cellular states and responses under diverse biological conditions, and data-driven virtual cell models that integrate multi-omics and spatial data.
- cutting-edge dynamical systems modelling, agent-based modelling, parameter identification and uncertainty modelling.
- advanced methods for analysing high-dimensional cellular data, including topological data analysis (TDA, such as Mapper), manifold learning, and statistical learning approaches.
A Masters or Bachelors degree in mathematics or statistics is required.
Supervisors: Prof Jennifer Flegg; Dr Heejung Shim; A/Prof Robyn Araujo
Project Commencement: 2025 & 2026
Funding: University of Melbourne scholarship through standard application process (deadlines: Round 1 – 1 Oct 2025; Round 2 – 1 Feb 2026); alternative funding may also be available - please contact for details.
Interested candidates should submit a Cover Letter, outlining their background and interested research areas, and their CV as well as academic transcripts, via this survey. We will get in touch once these documents are received.
Expressions of interest are encouraged as soon as possible for consideration in the upcoming scholarship selection round (deadline: 1 October 2025).
Details of the full application process and deadlines can be found here: https://study.unimelb.edu.au/find/courses/graduate/doctor-of-philosophy-science/how-to-apply/#nav
PhD Scholarships at Monash University
Do cutting-edge research at the frontiers of Whole Cell Modelling!
The MACSYS Node at Monash University has multiple PhD Scholarships available to work on some exciting projects!
- $41,753 p.a. stipend
- PhD: 3.5 to 4 years
- Additional funding available to support travel and advanced training
- Collaborate with MACSYS Researchers at four other universities
Projects include:
Integrative Modelling of the Bacterial Cell Envelope - From Molecular Structure to Metabolic Function: The cell envelope is the interface between a bacterial cell and its environment. MACSYS is currently modelling the structure and function of these cell envelopes for several bacterial species. The most powerful models have several parameters set from experimental observations, in this case data gathered through the use of electron-microscopy, proteomics and metabolomics. This project will study large protein secretion systems, drug-efflux pumps and lipid transport towers to provide means to integrate spatial information and metabolic movements across the cell envelope, to help inform mathematical models that integrate all of the envelope's function.
Uncovering RNA-RNA Networks in the Regulation of Bacterial Surface Proteins: Bacterial cell surfaces are studded with various proteins that permit or prevent small molecule movement into the cytoplasm. In order to access nutrients from their environments, bacterial cells regulate the synthesis and assembly of these cell surface proteins. A major and complex means by which bacterial gene expression is regulated to control surface protein production depends on RNA-RNA interactions to modulate protein translation. This project will use RNA cross-linking technology to understand all of the RNA-mediated control elements that contribute to the system of regulation that links metabolic needs with gene expression and cell surface remodelling.
- Contact: trevor.lithgow@monash.edu or kj.goh@monash.edu
Systems Biology of Bacterial Defence - Integrating Multi-Omics to Model Microbial Survival: Outside of optimal laboratory conditions, bacterial cells face dangers such as bacteriophages, protein toxins delivered from other microbes, antibiotic drugs and toxic chemicals, as well as antibodies in infection contexts. We have gathered libraries of phage and compounds to create test environments to trigger bacterial responses. Using transcriptomic, proteomic and metabolomic analyses, we will monitor the responsiveness of several bacterial species to these various dangers, to inform the design of, and test, mathematical models that will be generally applicable across a larger cross-section of important species of bacteria.
- Contact: trevor.lithgow@monash.edu or mike.mcdonald@monash.edu
Modelling Evolution - Predicting Bacterial Adaptation Using Whole-Cell Models: Bacterial populations evolve in response to selective pressures such as bacteriophages, antimicrobial agents, interspecies interactions, and host immune responses. In this project, you will use whole cell mathematical models (WCMs) to generate predictions about evolutionary outcomes under defined conditions, then design and run bacterial evolution experiments to test those predictions. By comparing model forecasts with genomic and phenotypic data from the evolving populations, you will test whether a deep understanding of the cell can inform predictions of bacterial adaptation.
- Contact: mike.mcdonald@monash.edu or trevor.lithgow@monash.edu