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🎓 Computational Mathematics PhDs

Numerical Simulation of Biological Interfaces and Elastic Surfaces in Fluid Flows
Freiberg University of Mining and Technology Prof. Dr. Sebastian Aland 🎓 Computational Mathematics 🎓 Engineering Mathematics

Explore the development of mathematical models and simulations of biological interfaces interacting with fluids. Develop and implement finite element codes to study elastic surfaces in fluid flows, gaining insights into…

This research advances understanding of biological processes by modeling the fluid-elastic interface interactions fundamental to cellular m…

2616+ citations · h25
Numerical Simulation of Surfaces and Evolving Geometries Scientific Computing Cells and Membranes
Simulation and Modelling of Mixing in Wet and Cohesive Powders
The University of Manchester Dr Anthony Thornton 🎓 Applied Mathematics 🎓 Computational Mathematics

Explore particle-based simulations to understand wet and cohesive powders central to multiple industries. Develop efficient reduced-order models and optimization approaches to improve predictions and mixing quality in r…

This research addresses critical challenges in predicting and controlling the behavior of wet and cohesive powders, which impact pharmaceut…

3120+ citations · h29
Multiscale modelling Granular Materials Self-healing materials
Near-Resonance-Informed Parallel Methods for Nonlinear Oscillatory PDE Models
University of Surrey Dr Bin Cheng 🎓 Applied Mathematics 🎓 Computational Mathematics Deadline: 04 May 2026

Explore numerical methods that exploit near-resonance theory to accelerate nonlinear oscillatory PDE simulations in parallel computing. Develop and test algorithms that improve speed and accuracy for applications in flu…

This research advances computational techniques essential for climate prediction, fluid simulation, and geophysical modelling by enabling a…

281+ citations · h11
Partial Differential Equations Geophysics Numerical Analysis Applied Mathematics
: Spatial Artificial Intelligence for Hyperspectral Image Analysis
University of Bath Prof Matthew Nunes, Dr Matthias Ehrhardt 🎓 Computational Mathematics 🎓 Computer Vision Deadline: 30 Apr 2026

Funded PhD at the University of Bath developing spatially-aware AI and machine learning methods for hyperspectral image analysis across scientific and industrial applications.

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.

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.

Digital Twinning for Smart Resin Infusion and Curing in Wind Turbine Blades via Embedded Fibre Optic Sensors and Physics-Informed Machine Learning
University of Hull Prof James Gilbert (University of Hull), Dr Hatice Sas (University of Sheffield) 🎓 Artificial Intelligence 🎓 Computational Mathematics

This fully-funded PhD develops a digital twin of the resin infusion and curing process in wind turbine blade manufacturing using embedded fibre optic sensors and physics-informed machine learning. The project aims to pr…

Dynamical symmetry breaking and restoration in closed quantum systems
Coventry University Prof Colin Rylands 🎓 Computational Mathematics 🎓 Data Analysis Deadline: 29 Mar 2026

This PhD investigates local dynamical symmetry breaking and restoration in closed many-body quantum systems. The project combines analytic and numerical techniques to explore universal aspects of symmetry in non-equilib…

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.