Bond graph model generation from molecular dynamics simulations

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. The Auckland Bioengineering Institute (ABI) applies engineering and technical innovation to advancing medical care, human capability, and understanding of human physiology. Research spans artificial intelligence, implantable devices, and digital human models, contributing to personalised medicine and global healthcare innovation.

Bachelor’s or Master’s degree in Engineering, Physics, or a related field
Experience with Python is highly desirable

Applications accepted all year round
Apply via University of Auckland postgraduate research application system
Refer to project listing on institute website