Research covers key areas of theoretical and applied statistics. This reaches from the study of statistical methodologies in statistical learning, spatial models, functional data to applications in medicine, biology, geoscience, finance and insurance. Applied research is often interdisciplinary benefitting from strong collaborations with researchers in other disciplines at the University of Leeds and externally, including public and private institutions. The Leeds Institute of Data Analytics and the affiliation with Alan Turing Institute guarantee a vibrant research environment with many opportunities for training and interaction with leading researchers in the field.

We are delighted to offer a fully funded PhD studentship and applications are invited from strongly motivated and academically excellent candidates for PhD study in our Statistics department, within these strategic priority Research areas:

·      Bayesian trees, modelling and prediction of extremes, machine learning

·      Wavelets; statistical bioinformatics, survival analysis

·      Machine learning, frequency data

·      Networks and their biomedical applications

·      Statistical bioinformatics, statistical genetics, epidemiology, high-dimensional data

·      Statistics applications in radiocarbon calibration, geoscience and archaeology

·      Bayesian tree models, applications of statistical learning in actuarial and climate sciences

·      Robustness and regularization; spatial and spatial-temporal processes; shape and image analysis

·      Functional data analysis, longitudinal data analysis, survival models

·      Collective behaviour and intelligence, movement and behavioural ecology

·      Directional statistics, image and shape analysis, spatio-temporal modelling

·      Model-based clustering, Bayesian inference for censored data, mixture of experts

·      Data science applications in medicine; computer vision, high-dimensional data

·      Applied statistics in life sciences, health and urban analytics

·      Statistical computing, Gaussian process emulators, machine learning, climate science

Please visit our website find out more about these research areas and eligible academic supervisors including how to contact them directly.