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Colleges

Doctoral research

Browse a list of current PhD opportunities in mathematical sciences for doctoral researchers. Please get in touch with our members for further details of supervisory availability. 

Description
Supervisor
Funding
Decision making for stratified medicine life cycle
Stratified medicine is at the cutting edge of a new era in healthcare, which targets to a specific patient population on the basis of a companion diagnostic (such as a biomarker) to predict treatment ...
Yang Yang
Self Funded
Decision making for stratified medicine life cycle
Stratified medicine is at the cutting edge of a new era in healthcare, which targets to a specific patient population on the basis of a companion diagnostic (such as a biomarker) to predict treatment ...
Yang Yang
Self Funded
Ambient Vibration-Based Calibration of Finite Element Models of Bridges
Objective: The primary objective of this project is to develop a novel method for calibrating Finite Element models of bridges using ambient vibration data and drone imagery. This method will leverage...
Michael Rustell
Self Funded
Bridging the Gap: Integrating Neural Radiance Fields and Micro-drones for Enhanced 3D Volumetric Finite Element Analysis
Objective: The central objective of this project is the innovative deployment of Neural Radiance Fields (NeRFs) and micro-drones in the process of 3D volumetric Finite Element modelling of bridges. Th...
Michael Rustell
Self Funded
Development and Validation of Security Metrics and Predictive Models for Blockchain Ecosystems
Background: Blockchain technology is a transformative innovation that has the potential to disrupt various sectors including finance, healthcare, and governance. However, with its growing adoption, se...
Self Funded
Autonomous Drone Surveys and Convolutional Neural Networks for Bridge Maintenance: A Predictive Approach Using Finite Element Analysis
Objective: The primary objective of this research is to develop a comprehensive framework for bridge maintenance that integrates autonomous drone surveys, convolutional neural networks (CNNs), and Fin...
Michael Rustell
Self Funded
Automatic computational fluid-dynamics
Computational fluid-dynamics (CFD) is undergoing a revolution from steady to high-fidelity unsteady methods.  A key time limitation to running CFD is in setting up a case to be run and processing data...
James Tyacke
Self Funded
Generative models with diffusion
The powerful engines behind synthetic data generation in AI are diffusion models, aka, stochastic differential equations. A success story that draws a lot of public attention recently is the generatio...
Self Funded