PhD: Integrating Palaeontological Data in Phylogenetic Analysis – Developing a Principled Statistical Model for Morphological Evolution

There is no substitute for palaeontological data in the reconstruction of deep evolutionary history. Phylogenetic analysis plays a key role in converting morphological observations to biological insights, but current approaches (parsimony or the Mk model) do not provide a satisfactory representation of phenotypic evolution.

This project will develop an explicit statistical model of morphological evolution, which will allow data from fossil organisms to be interrogated with the same rigour applied to genetic sequences – leading to quantitative statistical tests of diverse hypotheses of biological relationship and evolutionary processes.

Full training will be provided in widely-used statistical techniques (Markov processes, Bayesian inference, applied phylogenetic methods) and programming frameworks (Java, R), alongside specialist training in morphological and palaeontological data analysis; a mathematical or palaeontological background is not essential.

Further details are available through the NERC Iapetus website (iapetus.ac.uk) or by contacting Martin Smith (martin.smith@durham.ac.uk).