Machine Learning methods are becoming more and more widely used in nuclear reactor physics calculations for various purposes. In this project, we will use the computing resources to generate training data using Monte Carlo reactor physics codes, such as Serpent 2 and OpenMC, and create neural network models of nuclear reactors that allow for rapid fuel cycle optimisations, and optimisations of design and safety margins.