Theoretical & Computational Biophysics
Our vision is to use theoretical techniques to tackle a variety of problems in biophysics, with applications throughout biology, healthcare, imaging, spectroscopy and sensing. Our work, approaches and techniques are diverse and include biophysical modelling, computer simulation, machine learning, data science, GPU programming, dynamical systems analysis and automatic image analysis.
We are a cross-cutting theme with applications across all other themes in the Biomedical Physics group and beyond. Current group projects include:
- Mathematical modelling of membranes and membrane-bound proteins [Peter Petrov]
- Simulations of early embryogenesis [David Richards]
- Simulating how the environment influences the evolutionary fate of an expanding population [Wolfram Möbius]
- Machine learning of microglia state [David Richards]
- Computational imaging [Dave Phillips]
- Magnetoreception in animals [Daniel Kattnig]
- Image analysis of fungal growth [David Richards]