Bond graph model generation from molecular dynamics simulations

Dr Jarrah Dowrick, Dr Kenneth Tran

Applications accepted all year round

Awaiting Funding Decision/Possible External Funding

About the Project

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.