PhD: Can the past predict the future? The potential to persist and diversify using the shark phylogeny

Diversity is unevenly distributed across the tree of life. What traits determine a clade’s capacity to persist and diversify? This PhD project will address this fundamental question using sharks as a model, taking advantage of their long evolutionary history and abundant fossil record, and building upon novel statistical and artificial intelligence methods. The specific objectives of this project include: a) to build a shark phylogeny using data on fossil and extant species; and b) to test the extent to which traits rooted in the deep time affect speciation and survival potential.

The selected candidate will have the opportunity to learn Bayesian and deep learning methods by working alongside co-supervisor Prof. Daniele Silvestro (University of Fribourg, Switzerland) and to do international fieldwork to expand an existing fossil shark dataset. Additionally, the student will be offered ample opportunities to learn from world-leading experts in palaeontology, ecology and conservation by participating in research retreats and symposia with different research groups and attending national and international meetings.