Current research degree projects
Explore our current postgraduate research degree and PhD opportunities.
374 research degree projects
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Electronics and Computer Science | Engineering | Physics and astronomy
MEMS/NEMS-integrated ultralow stand-by power quantum circuits
Novel Micro/Nano-Electro-Mechanical Systems (MEMS/NEMS) switches will be developed to significantly reduce overall power consumption of integrated quantum circuits. The MEMS/NEMS switches will be optimised for low temperature operation and will be integrated with existing quantum circuits to evaluate the energy efficiency of the systems. -
Mathematical sciences
Quantum computing and optimisation for large-scale energy system planning under uncertainty
This project explores how quantum computing can transform energy system planning for a net-zero Europe. By integrating quantum and classical optimisation methods, it will address uncertainty in renewable generation and develop scalable algorithms for large-scale stochastic models, advancing both optimisation theory and practical tools for the energy transition. -
Chemistry and Chemical Engineering | Mathematical sciences | Physics and astronomy
Quantum optimal control for symmetry-based NMR sequences
Symmetry is a powerful tool for selection of NMR interaction and creation of correlated spin states. Many exquisite experiments are based on analytical calculation via average Hamiltonian or Floquet theory. A step change in efficiency and robustness may be obtained by combining Hamiltonian symmetry, periodicity and quantum optimal control. -
Engineering
Reconfigurable origami phononic metamaterials for on-chip quantum acoustics
How about building programmable acoustic highways on a chip! Using origami-inspired phononic lattices, we will switch topological edge paths to route phonons between quantum devices with low loss and high isolation. The project includes multi-scale computational modelling and MEMS fabrication, leading to scalable quantum sensing, multiplexed readout, and adaptive routing. -
Chemistry and Chemical Engineering | Biological sciences | Physics and astronomy
Quantum optimal control for long-lived NMR methods
NMR on Long-Lived States (LLS) and Long-Lived Coherences (LLC) offers an approach for extending the lifetime for entangled nuclear spin states. A new theoretical model will be developed, with the aim to predict and optimise experimental lifetimes, aided by quantum optimal control methods. -
Electronics and Computer Science | Engineering | Mathematical sciences | Physics and astronomy
Qubit efficient quantum optimization and applications to industrial problems
The main challenge in the adoption of quantum computing is the gap between algorithmic requirements and current quantum hardware. In this project, you will codevelop novel qubit efficient quantum approaches and techniques that can be used to solve optimization problems and apply them to logistics, pharma, transport, or manufacturing industries. -
Engineering | Physics and astronomy | Geography and environmental science
Quantum levitated mechanics for GPS-denied autonomous underwater vehicle navigation
This project will advance levitated optomechanical technology, specifically a levitated gradiometer, through early-stage development for autonomous underwater vehicles. You will contribute to the design, modelling, and experimental realisation of a prototype levitated gradiometer comprising two (or four) levitated optomechanical sensors stabilised by an optical interferometer for common-mode noise rejection. -
Physics and astronomy
2D materials as quantum sensors
Quantum materials such as superconducting magic-angle twisted bilayer graphene exhibit exceptional sensitivity to external stimuli, offering a unique platform for quantum sensing. This project develops 2D material-based membrane sensors for single-photon detection and noise spectroscopy, integrating nanoelectromechanical and quantum photonic functionalities into a unified, energy-efficient platform for next-generation quantum technologies. -
Engineering
Quantum-enabled memristors for neural interface engineering
Shape the future of neuro-controlled medical devices using quantum memristors as artificial synapses. Gain hands-on experience in micro/nano-fabrication, quantum state characterisation, neuromorphic circuits, and biohybrid interfaces, developing the critical neuromorphic interfaces that transform healthcare technologies to think, learn, and move like natural human body. -
Engineering
Sparse variational quantum machine learning
Variational quantum algorithms (VQAs) are hybrid classical-quantum machine learning methods designed to optimally utilize current quantum hardware, which remains limited by noise, limiting the number of computational operations. This project will adapt methods from sparse optimization to adapt the order and choice of the fundamental computations in VQAs.