During operations of a nuclear reactor, neutron flux measurements show fluctuations around the expected mean values. These fluctuations, referred to as neutron noise, may be due to a variety of perturbations such as mechanical vibrations of core internals, disturbances in the coolant flow, etc. From the analysis of the neutron noise, anomalous patterns can be identified at an early stage, so that appropriate actions can be taken before dangerous situations arise. Neutron noise-based monitoring subsequently contributes to enhanced safety. For this purpose, the reactor transfer function, which describes the core response to any possible perturbation, is most often required. The modelling of the reactor transfer function can be based on the Boltzmann equation for the neutron population in the system, while the possible perturbations are expressed in terms of changes in the neutron cross-sections. Most of the past work in this area relies on neutron diffusion theory [1]. However, recent efforts focus on the development of advanced computational capabilities in order to provide more detailed simulations and to assess the limitations of the diffusion approximation for neutron noise applications [2, 3, 4].