Bond graph model generation from molecular dynamics simulations
Eligible for funding* | PhD
Genome-wide association studies (GWAS) have transformed our understanding of disease risk, but translating genetic variation into mechanistic insight remains a major challenge. In particular, we lack systematic tools for converting molecular-level structural dynamics into interpretable, predictive physiological models.
As part of this project, you will develop a bottom-up computational workflow to extract thermodynamically consistent bond graph models directly from molecular dynamics (MD) simulations of proteins. Bond graphs provide a framework for describing the flow and exchange of energy across physical domains, making them a powerful bridge between molecular biophysics and systems-level modelling.
This project aims to create a workflow that connects molecular-scale dynamics to functional physiological behaviour.
Desired skills
Bachelor’s or Master’s degree in Engineering, Physics, or a related field. Experience with Python is highly desirable.
Contact and supervisors
For more information or to apply for this project, please follow the link to the supervisor below:
Contact/Main supervisor
Supporting Supervisors
- Kenneth Tran
- Peng Du
Eligible for funding*
This project is eligible for funding but is subject to eligibility criteria & funding availability.
Page expires: 11 September 2026