The goal of this project is to investigate new methods for using structured information about language variation in order to improve multilingual natural language processing models. The first part of the project is aimed at basic research on how to represent linguistic information about languages in a way that is maximally useful to neural models, while the second part of the project is concerned with applying these representations to practical tasks in natural language processing, such as machine translation and morphosyntactic analysis.