We are a research group at the MRC Laboratory of Molecular Biology in Cambridge, UK working on improving molecular simulations.
Molecular dynamics has shown success in obtaining biological insights by providing mechanistic interpretations of experimental data. However, the force fields used to describe how the atoms interact are biased towards keeping folded proteins folded and fail when applied to disordered proteins or protein aggregation. The idea of using the technique of automatic differentiation, most commonly used to train neural networks, to improve force fields is called differentiable molecular simulation (DMS). It overcomes the limitations of other methods by allowing multiple parameters to be tuned at once.
We aim to use DMS to improve all-atom force fields so they can work across a variety of protein systems, allowing us to answer questions of biological importance involving disordered proteins and disease-associated protein aggregation. We also aim to develop new machine learning interatomic potentials (MLIP) that are fast enough to simulate biomolecules. The next few decades will see compute resources increase to the point where simulations at biologically relevant length and time scales become routine. It is crucial that we have accurate physical models available to take advantage of this and to probe the molecular basis of life.
We are currently looking to grow the group!
If you are interested in a postdoc position, please contact Joe informally. We welcome applicants with experience in programming, computational chemistry, physical simulation or machine learning. We are also interested in helping people apply for fellowships to obtain their own funding.
PhD applications are handled as part of the LMB PhD program. Applications are currently closed.
University of Cambridge students can also apply to do part III projects in the group.
jgreener at mrc-lmb.cam.ac.uk
Joe Greener
MRC Laboratory of Molecular Biology
Francis Crick Avenue
Cambridge Biomedical Campus
Cambridge
CB2 0QH
United Kingdom
tel: +44 (0)1223 267068