Neural Network Proton transport

Development and validation of neural network methods for solving the forward problem in proton transport. Initially focusing on 1D, the project will explore the application of neural networks to accurately model and predict the interactions of radiation with tissue. We also aim to leverage the strengths of neural networks for inverse problems exploring the potential of neural networks to easily calibrate against experimental and clinical data and ultimately optimise complex treatment plans. Integration of neural network techniques with SDE models for the forward problem could also provide a robust framework for quantifying uncertainties in proton transport.