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🎓 Mathematical Modelling PhDs

Optimisation of Polymer Flooding Strategy During the Energy Transition
Heriot-Watt University Dr Alan Beteta; Prof Ken Sorbie 🎓 Applied Chemistry 🎓 Chemical Physics Deadline: 24 Apr 2026

Fully funded PhD using simulation and modelling to optimise polymer flooding for improved oil recovery and reduced carbon emissions.

Quantifying animal movement patterns and behavioural interactions in a changing world
University of Bristol Prof Andy Radford; Prof Simon Griffith; Prof Luca Giuggioli 🎓 Data Analysis 🎓 Ecology Deadline: 19 Apr 2026

Funded PhD at the University of Bristol combining mathematical modelling and empirical data to study animal movement and behavioural interactions in changing environments.

Multi-terminal HVDC Control and Operation Strategies for Offshore Wind Farms
Loughborough University Dr Zhengyu Lin, Dr Dong Chen, Dr Francisco Gonzalez-Longatt 🎓 Control Systems 🎓 Data Analysis

This PhD develops control and operational strategies for multi-terminal HVDC (MT-HVDC) networks in offshore wind, addressing vendor interoperability and system scalability using advanced simulations and industrial valid…

Single-turbine scale quantification of wake turbulence
Loughborough University Prof Chris Keylock, Dr Yi Li, Prof Michele Guala 🎓 Aerospace Engineering 🎓 Applied Mathematics

This PhD quantifies single-turbine wake turbulence to improve understanding of flow physics, aerodynamic interactions, and impacts on downwind turbines, combining numerical simulation, data analysis, and model developme…

Lifecycle Optimisation of Wind Farms using Machine-Learning Models Enhanced with Numerical Modelling
Durham University Dr Majid Bastankhah, Dr Nima Gerami-Seresht 🎓 Aerospace Engineering 🎓 Computational Mathematics

This fully-funded PhD focuses on enhancing wind farm performance and lifespan using machine-learning models integrated with numerical simulations to optimise turbine cluster aerodynamics and operational efficiency.

Aeroelasticity and Dynamics of Deployable Space Structures
The University of Manchester Dr Ajay Harish 🎓 Aerospace Engineering 🎓 Dynamics

This PhD investigates the coupled aeroelastic and dynamic behaviour of deployable space structures, such as solar arrays and antennas, to understand and optimize deployment reliability, vibration modes, and operational …

Aeroelasticity and Aerodynamics of Badminton Shuttle
The University of Manchester Dr Ajay Harish, Dr K Katnam 🎓 Aerospace Engineering 🎓 Bioengineering

This PhD investigates the coupled aeroelastic and aerodynamic behaviour of badminton shuttles, combining computational modelling and experimental analysis to predict flight stability, drag, and performance.

Modelling stroke progression and treatment in the brain
University of Bristol Prof Stephen Payne 🎓 Applied Mathematics 🎓 Biomedical Engineering

This PhD develops computational models to simulate stroke progression and treatment, incorporating individual patient factors to improve predictive accuracy and support targeted clinical interventions.

How does sleep affect your chance of brain disease?
University of Bristol Prof Stephen Payne 🎓 Applied Mathematics 🎓 Biomedical Engineering

This PhD develops the first multiscale mathematical model of sleep to study how individual sleep patterns influence lifetime brain health, including risks of diseases such as dementia.

Deep learning for cardiac medical image analysis
The University of Auckland Dr J Zhao 🎓 Artificial Intelligence 🎓 Biomedical Engineering Deadline: 19 Aug 2026

PhD project at the University of Auckland applying deep learning to cardiac CT and MRI analysis. Focuses on segmentation, disease modelling, and biomarker extraction to improve diagnosis and clinical decision-making in …

Gas flow Magnetic Resonance Imaging of the upper airway and Computational Fluid Dynamic modelling of airflow during Above Cuff Vocalisation
University of Leeds Dr Zinedine Khatir 🎓 Data Science 🎓 Dynamics Deadline: 08 Apr 2026

Funded CDT PhD at University of Leeds combining gas flow MRI and CFD to model airflow during Above Cuff Vocalisation in tracheostomy patients, providing evidence-based guidance for safe and effective clinical applicatio…

The Self-Driving Microscope: Predicting Stochastic Failure in Solid-State Batteries using Physics-Informed AI (Ref: M34Impact-MSE2)
University of Greenwich London, United Kingdom Dr James Le Houx, Dr Andrew Kao, Dr Mikhail Poluektov 🎓 Computational Mathematics 🎓 Computational Physics Deadline: 17 Apr 2026

Funded PhD at the University of Greenwich developing physics-informed AI to predict failure in solid-state batteries using X-ray imaging, simulations, and generative models.