PhD Research Students

The Department of Biostatistics offers supervision to PhD students in a wide variety of research areas.  Particular areas of expertise include survival analysis, multilevel modelling, joint modelling of longitudinal and time to event data, statistical epidemiology, structural and functional imaging, meta-analysis, pharmacogenetics, statistical performance monitoring, randomised controlled trials and pharmacokinetics, pharmacodynamics and personalised dosing algorithms.

Potential PhD Projects in Biostatistics:

Statistical approaches to analyse multivariate brain data

Analysis of dental caries data

Sampling techniques to characterise the spatial distribution of microstructures

Statistical shape modeling of symmetry and asymmetry in brain variability

Development and application of methodology for the detection of expression quantitative trait loci in multiple tissues (Dr. Andrew Morris)

This project will focus on the development of novel methodology for the joint analysis of gene expression from multiple cell types obtained from the same individuals. The approach will be extended to genetic data obtained through imputation.

The development of stochastic control algorithms for personalised dosing (Dr. Steven Lane).

Stochastic control algorithms that use pharmacokinetic information have been developed to estimate optimum doses for individual patients. The aim of this proposed research is to extend the dose estimation algorithms based on pharmacokinetics to drugs whose response are influenced by pharmacodynamic considerations.

The development of stochastic control algorithms for paediatric dosing (Dr. Steven Lane).

The proposed project aims to compare stochastic control algorithms with other potential methods of bridging (e.g. allometric scaling, which allows PK parameters to be adapted for body weight). The updating of PK parameters as the dose estimation process progresses will be investigated.

Multivariate modelling approach for search and evaluation of prognostic markers in cross-sectional observational studies (Dr. Gabriela Czanner).

The proposed project will develop statistical inference for prognostic measures within the framework of generalized linear models (such as logistic regression) and all developed methods will be applied to clinical data from malaria retinopathy studies. Possible extensions include longitudinally collected data and repeated measures from both eyes.

Multivariate modelling approach to image data from ophthalmology (Dr. Gabriela Czanner).

This project focuses on the development of spatial analysis tools to quantify retinal damage (e.g. leakage) from fluorescine angiography retinal images.

Evidence synthesis for biomarker validity (Dr. Andrea Jorgensen).

A biomarker-stratified-trial is the gold standard for testing the clinical utility of a biomarker-guided approach to treatment. Lack of such trials is considered to be one of the main obstacles delaying the translation of pharmacogenetic discoveries into clinical practice. This research project will explore how robust must the evidence of biomarker validity be to proceed to a biomarker stratified trial and how strong must the evidence be to rule out a biomarker trial on ethical grounds.

Meta-analyses of pharmacogenetic studies (Dr. Andrea Jorgensen).

This project will undertake a review of the pharmacogenetic literature in widely studied disease areas (e.g., cardiovascular disease) to determine the obstacles, which are hindering the potential for conducting large, well-powered meta-analyses. Methodologies for increasing the number of included studies will be explored, and guidelines will be developed to assist those embarking on meta-analyses in the future.

Causal mediation analysis for Epilepsy (Dr. Ruwanthi Kolamunnage).

The aim of this PhD project is to develop methods to estimate the causal effect of longitudinal QoL measurements on anti-epileptic drug treatment failure (allowing for competing reasons).

If you are interested in studying for a PhD within the Department of Biostatistics, please contact Dr Jamie Kirkham