Paul Kirk
Contact
Paul Kirk – paul.kirk@mrc-bsu.cam.ac.uk
Research Interests
I am a group leader at the MRC Biostatistics Unit, with research interests in biostatistical machine learning. Application areas range from characterising the RNA landscape of the human placenta in health and disease, to modelling spatial proteomics data, to discovering molecular signatures in cardiometabolic syndrome, to understanding properties of Bayesian nonparametric models that are commonly used in molecular biology and precision medicine.
My group’s interests are in the areas of latent structure discovery (including clustering and dimension reduction techniques), as well as flexible prediction models. We are crucially interested in probabilistic machine learning and nonparametric techniques that enable rigorous and reproducible analyses to be performed. To this end, we typically work within the Bayesian formalism, which enables principled uncertainty quantification, as well as the incorporation of prior biomedical knowledge and beliefs.
PhD Supervision
My previous PhD students have gone on to successful positions at Google and the University of Oxford. You can hear what one of my current students, Stephen Coleman, thinks about his PhD experiences, as well as read a brief comment from one of my previous students regarding her experiences of me as a supervisor.
Supervision includes regular one-to-one meetings, as well as weekly group meetings where students have the opportunity to practise presentations, interact with other group members, and learn about the activities of other members of my group.
Potential PhD projects
I have in mind 2 possible PhD projects, one co-supervised by Sach Mukherjee. I/we anticipate that these would be developed jointly with the PhD candidate (to reflect their interests and academic background), but the broad area would be a combination of: scalable inference for big data, Bayesian mixture models, high-dimensional statistics, and flexible predictive models.
How to apply
For details of the MRC BSU application process please see How to apply
To be considered for funding, applications need to be submitted to the University of Cambridge application system by 23:59 (GMT) on January 5th 2023