🎓 Computational Physics PhDs
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…
Explore how quantum computing can be harnessed to calculate nuclear level densities—key to understanding nuclear reactions and decays. Join a pioneering effort to develop quantum algorithms in a top UK research environm…
Explore advanced numerical methods that leverage near-resonance theory to simulate complex nonlinear oscillatory PDEs efficiently. Develop parallel-in-time algorithms optimized for scalability and energy efficiency in h…
Develop parallel numerical methods informed by near-resonance theory to accelerate nonlinear oscillatory PDE models. Explore how fast oscillations influence long-term dynamics and optimize algorithms for high-performanc…
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…
This PhD develops patient-specific multiphysics computational models to study the anatomy, biomechanics, haemodynamics, and electrophysiology of the right heart before and after pulmonary valve replacement in patients w…
Fibre composites are widely used in aerospace and wind turbines due to their light weight and high strength. This project will use coarse-grained modelling and molecular dynamics simulations to simulate network formatio…
Funded PhD at University of Southampton developing on-chip topological photonic crystals on silicon for applications in imaging, sensing, and computing. Combines theoretical modelling, simulation, and cleanroom fabricat…
Funded PhD at University of Southampton focusing on non-Hermitian topological physics, including exceptional points, skin effects, and topological phase transitions, combining theoretical modelling with electrical circu…
Fully funded PhD at University of Southampton exploring topological photonic quasicrystals. Combines theory, numerical simulation, and experimental fabrication to design novel optical materials with robust, topology-pro…
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.
This PhD focuses on developing charge-aware machine learning interatomic potentials for electrochemical applications, enabling accurate modelling of electrocatalytic systems with long-range electrostatic interactions.