Phd Student
CurrentMy PhD project aims to enable the rational design of bacterial antibiotic production, by creating an interface between computational and wet-lab biology. On the computational project, I have been applying machine learning to predict substrate properties from protein structures generated in Alphafold. Approaches used have included graph networks and convolutional neural networks, using Keras, TensorFlow and Pytorch Geometric, written in Python and R. The wet lab side of the project has included the development of molecular biology techniques for manipulation of large and complex DNA constructs, analytical chemistry of natural products (HPLC and Mass Spectrometry), as well as a range of supporting molecular biology techniques.