The genomes of organisms bear the footprint of their evolutionary history. By combining information from molecular sequences (genomes) with information from the fossil record (such as morphology), inferences about this evolutionary history can be obtained and placed in the right geological context. However, the fossil record is notoriously incomplete, and patterns of genome evolution vary substantially among species, providing important challenges to the study of ancient evolutionary events. Recent advances in Bayesian statistics allow probabilistic modelling of the uncertainties in fossils and genomic evolutionary rates, so that robust inferences about species divergence times can now be made. The Bayesian method has been used to solve mysteries such as the pattern of diversification of mammals after the End-Cretaceous mass extinction, or the time of origin of animals in the Proterozoic. In this project the student will work in the application and/or development of Bayesian MCMC statistical methods to study species divergences through time. The project will include the collection of genomic and morphology data from online databases, and the use of computer software for analysis. Experience in the use of statistical software (such as R) and computer programming would be an advantage. The project is suitable for students interested in genomics, palaeontology and Bayesian statistics.