Postgraduate Projects
Postgraduate Projects
The projects listed below are those which our academics are interested in supervising and are actively recruiting for the 2026-27 academic year. If you are interested in applying for one of these projects, please contact the lead supervisor directly to discuss this further before making your application for admission. Please note this list is of projects which do not have guaranteed funding; fully-funded projects are advertised separately on the Research studentships webpage.
This list is not exhaustive, so if you have another project in mind or would like to explore potential projects, please contact the academic you would like to work with well in advance of the admissions deadline stated on the course page. Information about the various areas of research covered by the department are listed on the Research webpage.
The projects are organised by primary research panel, so please select the relevant panel below and a list of projects will be displayed, organised by primary supervisor.
Multimodal Cardiovascular Digital Twins for Disease Prediction and Personalised Healthcare
Geometric Deep Learning for Cardiac Shape, Motion and Function Analysis
Scalable, Generalisable and Trustworthy AI for Global Cardiovascular Health
Anthropomorphic Robotic Hands with Artificial Muscles
Anthropomorphic Robotic Foot-Leg Systems for High-Fidelity Wearable Device Testing
Soft Robotic Organs for Next-Generation Medical Device Testing (co-supervisor Ryman Hashem)
Soft Bioelectronic Interfaces for Next-Generation Neuromodulation
Targeted Quantum Nanomaterials for Intracellular Biosensing
AI-Enabled Raman Imaging for Biomedical Discovery
Engineering Programmable Drug Delivery Systems
Engineering Soft Robotic Systems for Biomedical Applications
Engineering Nanoparticles for Ultrasensitive Disease Detection
Trustworthy GenAI for Medicines Safety and Regulatory Science: Reasoning over Evolving Graph-Structured Knowledge under Uncertainty
Development of Federated Personalised Foundation Models for Predicting Adverse Pregnancy Outcomes Using Real-World Evidence (Co-supervisor Lucy Mackillop, Nuffield Department of Women's & Reproductive Health)
Federated Learning for Global Infectious Disease Surveillance and Preparedness (Co-supervisor Esteban Garcia, Pandemic Sciences Institute).
AI Agents for Next-Generation Automated Liquid Handling in Cell Biology.
Fluid-Walled Microfluidic Platforms for Guiding Axonal Connectivity Across Discrete Neuronal Populations.
Reliable AI systems (failure detection, out-of-distribution, fairness, causality)
Adaptive AI (continuously learn from user or new data)
Vision-Language Modelling for medical imaging
AI for detecting or segmenting pathologies / tissues in medical images
Digital image correlation using surface geometry data from time-of-flight cameras and laser scanning
High-speed subpixel tracking of deformations using neuromorphic cameras
Integrated and differentiable full-field measurement and inverse modelling operators
Mechanosorptive timber creep characterisation using integrated projection-based Digital Volume Correlation
Developing earthen blocks with crosslinked starch binders to replace concrete blocks used for housing
Fe-SMA tie bar prestressing and reinforcement to prevent disaggregation in rubble masonry during earthquakes
Coastal flooding prediction and risk using RTide: Oxford's physics constrained machine learning model
The physics and statistics of rogue waves in the ocean
Understanding the system value of marine renewable energy
Observability algorithms for Structural Health Monitoring
Modelling the response of museum exhibits to dynamic excitations
Monitoring Offshore Structures
Damage Detection in Infrastructure Elements
Machine-learning accelerated predictions of wave-structure interaction
Floating offshore wind turbine platform survivability
Flexible, deformable wave energy converters
Hydrodynamics of hybrid wind-wave energy platforms
Reliable engineering use of vegetation for mitigating landslides and stabilising earthworks
Efficient hybrid methods for incorporating urban structure-soil-structure interaction effects in seismic structural design
Reduced-order models for optimising anchorage design for offshore renewables
Foundation systems for lunar and martian construction
A new generation of models to predict corrosion-fatigue and extend the service life of offshore wind turbines
Advanced computational fracture methods to predict concrete crushing and enable new recycling technologies
Resilient and sustainable use of advanced metal alloys in critical infrastructure
Additive manufacturing for next-generation structural capabilities
Ai-augmented design and equation discovery for performance prediction in complex structural systems
Structures in extreme environments where fatigue and corrosion pose reliability issues
Structural optimization under performance and sustainability constraints based on whole life assessment
Climate-positive building aligning with sustainability agendas (e.g., PAS 2080, Net Zero policies)
AI-driven material discoveries for new concrete products and their testing and validation
How breaking ocean waves contribute to mixing in the upper ocean
How internal ocean waves travel over long distances
How ocean wave crests produce sea spray at high wind speeds
High-fidelity numerical simulations of droplet aerobreakup
The development of rip currents in coastal waters
Water waves as analogues for quantum particles
Scalable optimisation-based methods for nonlinear control
Designing safe and stable learning-based control schemes
Combining synthetic biology and Artificial Intelligence for high-throughput engineering of Bacteria for sustainability applications.
Developing machine learning methods for predicting Antibiotic Resistance Evolution (AMR) with new robotic experimental platforms.
Engineering quantum mechanical effects in fluorescent proteins and other bioengineered sensors and actuators.
Control techniques for large-scale and high-throughput systems (Areas of research: control theory, multimodal matrix factorisations, optimisation; Application areas: particle accelerators, fusion reactors, smart manufacturing plants)
Data-based control for large ensembles of similar systems (Areas of research: control theory, robust control, behavioural theory, data-enabled control; Application areas: cybergenetic control, manufacturing, infrastructure)
Methods for control and characterisation of evolutionary processes (Areas of research: AI-driven control, graph theory, control theory; Application areas: biotechnology)
Hyper-local forecasting of solar power generation using irradiance sensor data, weather forecasts, and machine learning
Optimisation of energy storage connected to solar generation for cost and carbon savings
Solar forecasting, low cost irradiance sensing, and the influence of solar forecasts on control of battery energy storage systems
Unsupervised data-driven fault detection in battery systems.
Battery passports and the circular economy
Sodium-ion battery continuum modelling (co-supervisor Charles Monroe)
Scaling AI safety for multi-agent power system control
Hybrid Quantum-Classical Computing for Power System Optimisation
Power Grid Intelligence for AI Data Centres
Rethinking Internet infrastructure for AI workloads
Designing resilient digital infrastructure for disaster scenarios
Designing a truly net-zero Internet
Novel compute/ network chip architectures beyond clock frequency
Using novel/quantum accelerators for core network operations
Fast, efficient and compact quantum memories for feed-forward operations
Hybrid quantum networks based on quantum dot photon sources and atomic quantum memories
Circular and sustainable data centres
Circular economy of solar PV
Circular economy of wind turbines
Swarm Intelligence for Predictive Maintenance and Environmental Monitoring in Industrial Systems
Detecting AI Diffusion in the Global Health Workforce Using Large Language Models
AI for Automated Quantum Experiments – Quantum technologies and AI
Thermodynamics of nanoscale quantum devices – Quantum technologies and out-of-equilibrium thermodynamics
Quantum hardware for efficient learning – Quantum technologies
Site-Aware Digital Representations for Autonomous Robotics for Persistent Site Intelligence
Resource Allocation and Shared Intelligence in Site-Driven Robotics
Safety Assurance and Resilience for Infrastructure-Supported Robotics
Cross domain localisation between cameras, lidar and building floor plans
Building joint semantic object maps with robots and AR headsets (e.g. Meta Aria glasses)
See through the smoke: Joint motion tracking with vision and radar in challenging conditions
Monitoring crop yields with Gaussian Splatting
Task orientated robot exploration with language-orientated visual 3D maps
Generative AI-Enhanced Gamified Virtual Rehabilitation for Neuromuscular Disorder Therapy
Full body Haptic Device for Virtual Reality
Human–Robot–AI Collaboration for Personalised Assisted Physical Therapy
Human–Robot–AI Collaboration for Adaptive Soft Exoskeleton Control
Learning Tactile World Models for Dexterous Manipulation
AI-Driven Co-design of Soft Robot Morphology and Control
Learning-Based Control of Soft Robotic Manipulators
Learning Multimodal Representations for Vision, Proximity and Touch
Synthetic Tactile Data Generation for Robot Learning
Next-Generation Tactile Sensing for Embodied AI
Design of Soft Robots and soft sensing technologies
Intelligent Robotic Simulators for Occupational Therapy Training
Trustworthy AI and Swarm Intelligence for Multisensory Learning and Decision-Making on Resource-Constrained Edge Devices
Physics-Informed AI with Self-Sensing Actuating Materials for Cyber-Physical Security and Robotics
Energy-Aware Multisensory AI for Net-Zero Socio-Technical System
Resilient Multisensory Networks for Crisis Monitoring, Response and Recovery (Co-supervisor Noa Zilberman)
Multiphysics modelling of solid state batteries: from fundamental understanding of chemo-mechanial failure mechanisms to improved battery design
Mechanics of soft materials: bridging the gap between statistical mechanics and solid mechanics.
Chemo-mechanics of biodegradable polymers: understanding the couplings between mechanics and chemistry in biodegradable and sustainable plastics
Rate-dependent fracture of soft materials: experiments and multiscale modelling
Granular robots: design, fabrication, and simulation of active robotic grains to explore emergent cluster dynamics.
Fluidic robotic oscillators: probing the dynamics of bifurcations, chaos, and Hopf oscillations.
Mechanical metamaterials: unlocking shape-shifting wearable technologies.
One input, many outputs: harnessing mechanics to simplify control.
Environmental soft robotics: designing with sustainable and biodegradable materials.
Bio-inspired robotic swimmers with architected flexible skin
Deployable metastructures for targeted, programmed drug delivery
Rapid Measurement of Deep Earth Seismic Properties using Laser Transient Grating Spectroscopy in the Diamond Anvil Cell (co-supervisor Hauke Marquardt)
Understanding the evolution of thermal transport properties in fusion reactor armour materials using using Laser Transient Grating Spectroscopy (co-supervised by UKAEA)
Deformation behaviour of highly irradiated structural materials for fusion power (co-supervised by Edmund Tarleton)
Understanding hydrogen embrittlement at the micro-scale by combining crystal plasticity and insitu micro-scale hydrogen charging experiments
Hydrogen-embrittlement testing at high pressures and temperatures to predict material degradation in hydrogen-fuelled jet engines
Quantifying hydrogen-induced lattice strain using optical interferometry and insitu X-ray diffraction experiments
How does hydrogen alter the structure and behaviour of atomic scale defects? Leveraging combined X-ray Bragg Coherent Diffraction Imaging and Atomistic Simulations.
Fracture and fatigue in nuclear fission and fusion composites
Understanding the mechanical behaviour of alloys in cryogenic conditions for hydrogen storage
Development of AI tools in energy materials
3D imaging and diffraction of next generation of semiconductor devices
Degradation in the thermal and mechanical properties of nuclear materials
Critical experiments to unravel hydrogen-material interactions holding back hydrogen’s decarbonization potential
A new class of multi-physics finite element models to accelerate the energy transition: from Li-Ion batteries to hydrogen
Methods for characterising and enhancing the durability of Stereolithograpy (SLA) composites (collaboration with Stratasys Ltd.)
AI techniques for rapid prediction and qualification of recycled polymer blends.
Experimental and multiscale modelling approaches to the mechanics and degradation of additively manufactured foams.
Machine learning-based optimisation of powder bed fusion process parameters for bioresorbable composites.
Fatigue and degradation in bioresorbable lattice materials.
A 3D printed, bioresorbable osteotomy wedge.
Mass transport under mechanical load in bioresorbable particulate composites.
Sensor Fusion and ML for Robust Condition Monitoring of Wind Turbines and High-Performance Vehicles.
Building state-estimation tyre models, for high performance vehicles and pollution estimation.
Experimental investigation of high-temperature materials for hypersonic flight
Flows around hypersonic glide vehicles in ground testing facilities
Gas surface interaction of decomposing re-entry capsules
Optical measurement of plasma temperatures using physics informed machine learning (co-supervisor Joao Henriques)
Low cost microturbine design
Reducing uncertainty in aerodynamic probe measurements for transonic flows
Machine learning applied to supersonic nozzle optimisation
Superposition methods for film cooling applications in gas turbines
Improving overall cooling effectiveness measurement accuracy in gas turbine experiments
Spray Cooling for Rotating Machinery in High-Performance Motorsport Applications
High-Altitude Manoeuvrability of Hypersonic Glide Vehicles using Lateral Reaction Control Jets
Novel Heat Exchanger Architectures for Liquid Hydrogen-Powered Aircraft.
Cryogenic Phase-Change Heat Transfer for Thermal Management of Next-Generation Computing and Electronics.
Next Generation of Machine Learning-Enhanced Velocity and Temperature Wall Function for Separated Flows
Digital Twin Framework for Real-Time Life Prediction for Small Modular Reactors