Funded PhD Studentship in Statistics

Summary

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:

Georgios Aivaliotis: Bayesian trees, modelling and prediction of extremes, machine learning

Stuart Barber: wavelets; statistical bioinformatics, survival analysis

Leonid Bogachev: machine learning, frequency data

Luisa Cutillo: networks and their biomedical applications

Arief Gusnanto: statistical bioinformatics, statistical genetics, epidemiology, high-dimensional data

Tim Heaton: statistics applications in radiocarbon calibration, geoscience and archaeology

Lanpeng Ji: Bayesian tree models, applications of statistical learning in actuarial and climate sciences

John Kent: robustness and regularization; spatial and spatial-temporal processes; shape and image analysis

Haiyan Liu: functional data analysis, longitudinal data analysis, survival models

Richard Mann: collective behaviour and intelligence, movement and behavioural ecology

Kanti Mardia: directional statistics, image and shape analysis, spatio-temporal modelling

Elham Mirfarah: model-based clustering, Bayesian inference for censored data, mixture of experts

Sofya Titarenko: data science applications in medicine; computer vision, high-dimensional data

Seppo Virtanen: applied statistics in life sciences, health and urban analytics

Jochen Voss: statistical computing, Gaussian process emulators, machine learning, climate science

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.