Available Projects
The project list below helps self-funded and externally sponsored applicants (scholarship) connect with a prospective supervisor.
Applications are welcome from those who can support themselves or have funding already arranged. Such applications will go through the same level of academic assessment. Please see the fee arrangementsLink opens in a new window for PGR students.
EEG signal analysis in the home / away from the clinic: on the development of robust and efficient data analysis techniques
Electroencephalography (EEG) has significant potential for monitoring neurological health outside clinical environments, but real-world recordings are often affected by noise, artefacts, and variable usage conditions. This project will develop robust and efficient signal processing and AI-based analysis techniques for home-based EEG monitoring, enabling reliable assessment of brain activity and supporting future applications in neurological diagnosis, healthcare, and personalised medicine.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Use the link above to expand the project detail.
Batteries without the "forever chemicals"
Almost every lithium-ion battery is held together by PVDF, a 'forever chemical' processed in a toxic solvent, and regulators are closing in. Can we build better batteries without it? In this PhD you will design, process and test PFAS-free, water-processable binders for high-energy cathodes, and work out why some binders succeed where others fail. Polymer science, electrode engineering and electrochemistry, with a clear route to industry.
Primary supervisor: Dr Volkan Degirmenci - V.Degirmenci@warwick.ac.uk
Use the link above to expand the project detail.
Adaptive Control for Safe Human–Robot Collaboration
This project will develop adaptive control methods that enable robots to operate safely and effectively in changing environments and near human users. Building on previous research in robot safety, task prioritisation, collision avoidance and hard constraints, the work will investigate how sensing and real-time control can be combined to support flexible collaborative tasks. Methods will be validated experimentally using robot arms and representative end-effectors.
Primary supervisor: Khaled Al Khudir - Khaled.Al-Khudir@warwick.ac.uk
Use the link above to expand the project detail.
From wildfire smoke to alien skies: replacing a 1910 formula with physics-informed machine learning
A formula fitted in 1910 to oil drops still decides how climate models, pollution monitors and engineering software predict the motion of tiny airborne particles. But real particles such as soot, ash, viruses and nanoplastics are not spheres. Building on new theory from our group, you will combine fast molecular-level simulations with physics-informed machine learning to create an open tool that predicts how any nanoparticle moves, in any gas, from Earth's air to the skies of other worlds.
Primary supervisor: Duncan Lockerby - Duncan.Lockerby@warwick.ac.uk
Co-supervisor:TBD
Use the link above to expand the project detail.
Not all particles are spheres: tyre wear, nanoplastics and where air pollution really goes
Air-quality rules describe every particle by one number, its 'aerodynamic diameter', assuming shape does not matter. But the pollution now rising fastest, from brake and tyre wear, microplastics and nanomaterials, is made of flakes, fibres and fragments. You will develop new physics-based tools to predict how particles of any shape move near walls, where they are caught by filters, counted by sensors or deposited in the lung, and map when the one-number picture fails.
Primary supervisor: Duncan Lockerby - Duncan.Lockerby@warwick.ac.uk
Co-supervisor: TBD
Use the link above to expand the project detail.
Phenomenological modelling of human gait under vibration
How does the human body dynamically adapt when the ground beneath us vibrates? Human gait on vibrating surfaces produces challenging nonlinear dynamics, with implications for biomechanics, fall prevention, and the design of pedestrian structures. This project will use experimental data to develop a phenomenological model capturing effects of vibration exposure on gait dynamics. It is ideal for students fascinated by mathematical modelling, nonlinear dynamics, and gait analysis.
Primary supervisor: Bintian Lin - Bintian.Lin@warwick.ac.uk
Use the link above to expand the project detail.
Physics-informed AI for the flow of polymers, inks and biological fluids at the nanoscale
At the nanoscale, liquids jiggle: random molecular motion controls how jets break up, films rupture and droplets merge. Adding noise to the Navier–Stokes equations captures this for simple liquids like water, but no equations exist for complex liquids such as polymers, inks and biological fluids. You will use physics-informed machine learning, trained on molecular simulations, to discover them, and release the result as open-source software.
Primary supervisor: Duncan Lockerby - Duncan.Lockerby@warwick.ac.uk
Co-supervisor: James Sprittles (Mathematics)
Use the link above to expand the project detail.
Washing the sky: solving a 70-year-old puzzle about how rain cleans polluted air
Rain is the atmosphere's main way of removing fine-particle pollution, yet it clears these particles 10 to 100 times faster than theory predicts, a puzzle since the 1950s. Working with the Met Office, you will test a new explanation: at these scales air no longer behaves as a smooth fluid. You will model particles of realistic shape meeting falling raindrops and deliver a better rain-scavenging scheme for weather and climate models.
Primary supervisor: Duncan Lockerby - Duncan.Lockerby@warwick.ac.uk
Co-supervisor: James Sprittles (Maths)
Use the link above to expand the project detail.
Identifying fibrillation areas via modelling heterogeneous tissue to facilitate ventricular tachycardia ablation
The project aims to develop a framework to model the dynamics of heterogeneous tissue using multivariate electrogram signals. The developed framework should be integrated into the existing surgical procedure. The project ultimately aims to improve patient outcomes.
Primary supervisor: Igor Khovanov - I.Khovanov@warwick.ac.uk
Detecting and Tracking Changes in Behaviour for Health and Wellbeing
Changes in behaviour can provide early indicators of declining physical, cognitive, or mental health. This project will develop intelligent methods to detect and track behavioural changes using data from wearables, smartphones, and connected environments. By combining AI, data analytics, and digital health technologies, the research aims to enable personalised, proactive monitoring that supports earlier intervention, improved wellbeing, and independent living.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Use the link above to expand the project detail.
Video analysis of the behaviour of micro-organisms: development of automated behaviour monitoring techniques
Micro-organisms exhibit complex behaviours that provide valuable insights into biological processes, environmental responses, and cellular health. This project will develop automated video analysis techniques to detect, quantify, and track microorganism behaviour. Combining computer vision, image processing, and AI, the research will enable high-throughput, objective behavioural monitoring, supporting advances in biotechnology, microbiology, environmental science, and biomedical research.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Use the link above to expand the project detail.
Combining brain and behaviour measures for children with Autistic Spectrum Disorder
Autism Spectrum Disorder (ASD) is characterised by diverse cognitive, sensory, and behavioural differences, making personalised assessment and intervention challenging. This project will combine brain-based measures, such as EEG and neuroimaging, with behavioural and developmental assessments to better understand individual differences in ASD. The research aims to identify objective markers that support earlier diagnosis, personalised interventions, and improved outcomes for autistic children.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Use the link above to expand the project detail.
On the development on Blind Source Separation techniques with sparse signals: application to brain signal recordings
Brain recordings often contain mixtures of signals originating from multiple neural and non-neural sources. This project will develop advanced blind source separation techniques for sparse signals, enabling the reliable extraction of meaningful brain activity from complex recordings. By combining signal processing, optimisation, and machine learning, the research aims to improve the analysis of EEG and related neurophysiological data for neuroscience and healthcare applications.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Use the link above to expand the project detail.
Experimental Fluid Mechanics
Projects in experimental fluid mechanics are offered. The projects can include a computational and/or theoretical component. I supervise projects in most areas of fluid mechanics. The exact project area is normally decided upon after discussion with potential applicants, and depending on their particular interests.
Primary supervisor: Peter J. Thomas - P.J.Thomas@warwick.ac.uk
Co-supervisor: T.B.A.
Use the link above to expand the project detail.
Distributed Machine Learning for Collaborative Robotics
How can a team of robots learn, reason, and collaborate intelligently when communication is unreliable, bandwidth is limited, and computing resources are constrained? Distributed machine learning is enabling fleets of robots to share knowledge, coordinate decisions, and accomplish complex tasks without relying on a centralised AI system.
Primary supervisor: Zhenhui Yuan - Zhenhui.Yuan@warwick.ac.uk
Use the link above to expand the project detail.
Low-Latency Telepresence Robotics
What if you could physically control a robot thousands of miles away — or even on another planet — as if you were standing right there? Telepresence robotics is turning this science fiction into reality, enabling remote surgery, hazardous site inspection, and assistive care through immersive mixed-reality (XR) interfaces.
Primary supervisor: Zhenhui Yuan - Zhenhui.Yuan@warwick.ac.uk
Use the link above to expand the project detail.
Computational modelling of maternal glucose adaptation and fetal growth in pregnancy
The project will develop and apply tools to understand blood glucose regulation in pregnancy and help identify women at risk of maternal and fetal complications earlier. This project will combine dynamic modelling, time series analysis and machine learning to analyse clinical data and data from continuous glucose monitoring collected throughout pregnancy. You will investigate changes in glucose patterns and their links to gestational diabetes, fetal growth and labour complications.
Primary supervisor: Natasha Khovanova - N.Khovanova@warwick.ac.uk
Co-supervisor: Dimitris Grammatopoulos (Warwick Medical School)
Use the link above to expand the project detail.
Learning from nature to drive on Mars
How do you drive a rover on Mars, where sand is loose, gravity is weak and nobody can come and push? Nature has already solved similar problems: the textured skins and surfaces of animals manage grip and flow remarkably well. In this PhD you will design, 3D-print and test bio-inspired surface patterns, measuring how they control friction, traction and drag, and translate the best into wheel and surface concepts for planetary exploration.
Primary supervisor: Dr Volkan Degirmenci - V.Degirmenci@warwick.ac.uk
Use the link above to expand the project detail.
Printing with molecules: 3D architectures from metal-organic frameworks
What if we could print materials molecule by molecule? Metal-organic frameworks (MOFs) are crystalline 'molecular scaffolds' with enormous internal surface areas and tunable chemistry. In this PhD you will develop inks and printing routes, from inkjet to 3D printing, to turn MOFs into functional architectures for energy, sensing and electronics, and learn how molecular design translates into real device performance.
Primary supervisor: Dr Volkan Degirmenci - V.Degirmenci@warwick.ac.uk
Use the link above to expand the project detail.
Teaching zinc-air batteries to breathe in and out
Zinc-air batteries are cheap, safe and made from abundant elements, which makes them ideal for storing renewable energy. Two things hold them back: a sluggish air electrode and an unruly zinc anode. In this PhD you will design MOF-derived electrocatalysts for the oxygen reactions (OER/ORR) and engineer the zinc interface to stop dendrites, then bring both together in rechargeable cells that last.
Primary supervisor: Dr Volkan Degirmenci - V.Degirmenci@warwick.ac.uk
Use the link above to expand the project detail.
On-line tracking of C. elegans: the development of an automated real-time tracking platform
Caenorhabditis elegans is a widely used model organism for studying behaviour, neurobiology, ageing, and disease. This project will develop an automated real-time tracking platform capable of continuously monitoring worm movement and behaviour. Combining computer vision, image processing, and machine learning, the research aims to deliver accurate, high-throughput behavioural analysis to support biological discovery and experimental automation.
Primary supervisor: Christopher James - c.james@warwick.ac.uk
Use the link above to expand the project detail.
Identifying and Mitigating Power Grid Stability Risks from Artificial Intelligence Data Centres
Artificial intelligence (AI)-based technologies are being adopted across various sectors at an unprecedented scale. However, the computing resources required to run these algorithms, i.e., the AI data centers, are extremely power hungry, thus significantly increasing the burden on the electrical grid. The proposed PhD project will develop analytical methods to identify the threats from AI data centers to power grids and develop solutions to mitigate the risks.
Primary supervisor: Dr Subhash Lakshminarayana - Subhash.Lakshminarayana@warwick.ac.uk
Use the link above to expand the project detail.
3C-SiC - the renaissance of a wide bandgap material (x2 projects available)
3C-SiC is re-emerging as a wonder semiconductor material which is making strides in multiple different fields: a) power electronics, b) powerless hydrogen generation by photo-electro-chemical generation, c) non-toxic bio compatibility for in-vitro bioelectronics, d) high temperature CMOS, e) 3C-SiC MEMS sensors and e) quantum computing.
In this project, the students will develop 3C-SiC materials and develop device processing technology for power electronics applications.
Primary supervisor: Dr Vishal Shah - Email: Vishal.Shah@warwick.ac.uk
Use the link to explore the project in more detail.
The development of Silicon Carbide power semiconductor devices
Silicon carbide (SiC) power devices enable higher efficiency and power density than silicon in electric transport, renewables and fast chargers. This project will design and develop SiC MOSFET/diode structures, studying key energy losses and reliability mechanisms (RDS(on), switching, oxide/interface traps). Outcomes include optimised devices and guidelines for robust operation.
Primary supervisor: Professor Marina Antoniou - Email: Marina.Antoniou@warwick.ac.uk
Use the link to explore the project in more detail.
Dowel-laminated Bamboo: a new-generation, minimally-transformed engineered bamboo product
Join our research into this low-carbon, -cost and -capital technology with the potential to improve housing for millions in low- and middle-income countries. Dowel-laminated bamboo delivers a regularised section without incurring in the high waste, cost and glue-content of other engineered bamboo products, yet its possibilities have been underestimated and hence scantly researched or developed. This project will characterise its behaviour, explore its possibilities and optimise its performance.
Primary supervisor: Dr David Trujillo - Email: David.Trujillo@warwick.ac.uk
Co-supervisor: Dr Reyes Garcia
Use the link to explore the project in more detail.
Design rules for headed stud connectors welded within steel deck with the ribs parallel to the supporting beams
The objective of this project is to develop design rules for stud shear connectors in decking: with the ribs perpendicular to the supporting beams; or when crushed ends are introduced to the deck. It is planned that the results from this research will form the basis for UK design guides and/or Complimentary Information within the UK National Annex to EN 1994-1-1: 2025, which may be incorporated within the next generation of this European design standard.
Primary supervisor: Professor Stephen Hicks - Email: Stephen.J.Hicks@warwick.ac.uk
Use the link to explore the project in more detail.
Robotic Extrusion and Process Control for 3D Printing of Cementitious Materials
This project investigates the interactions between cementitious material rheology, robotic deposition and material extrusion, developing a controlled dispensing system to predict and optimise print quality. By linking material behaviour, deposition dynamics, and structural performance, the project aims to develop a framework for data-informed 3D printing of concrete, advancing automation, quality and precision in construction.
Primary supervisor: Dr Javier Munguia - Email:Javier.Munguia@warwick.ac.uk
Co-supervisor: Dr Reyes Garcia
Use the link to explore the project in more detail.
Electrical Drives and Power Converters for Electrical Vehicles and Renewable Generation
The goal of the project is to identify control challenges for specific applications due to advances in the supply chain and overcome them via advanced control and sensing methodologies.
Primary supervisor: Dr Oleh Kiselychnyk - Email: O.Kiselychnyk@warwick.ac.uk
Use the link to explore the project in more detail.
New low-carbon fire-resistant geopolymer concretes: a journey towards net zero in construction
This project aims to develop new low-carbon fire-resistant and thermal-resistant geopolymer concretes (i.e. concrete without cement) for applications in sustainable construction. Our team has strong collaborations with top research groups on geopolymers around the world (e.g. Monash University), so there is potential for placements and training abroad. Your training package will be tailored and agreed upon once you join our group.
Primary supervisor: Dr Reyes Garcia - Email: Reyes.Garcia@warwick.ac.uk
Use the link to explore the project in more detail.
Multisensory virtual reality for human assessment of built environments
Humans are highly sensitive yet imprecise in perceiving environmental stimuli. Every built environment presents a unique combination of sensory cues, resulting in complex human responses. This project aims to develop multisensory virtual reality simulations that integrate visual, auditory, and vibration stimuli, enabling people to evaluate built environments in a digital setting. Ultimately, the tools developed will help design environments that help people to thrive.
Primary supervisor: Dr Bintian Lin - Email: Bintian.Lin@warwick.ac.uk
Co-supervisor: Professor Stana Zivanovic
Use the link to explore the project in more detail.
Engineering emerging materials for quantum technologies
The aim of the project is to exploit electronic properties of nanoscale materials to discover and design novel materials for nanoelectronic applications. The ultimate goal of the research is to understand quantum transport through molecular structure such as single molecules, self-assembled monolayers, graphene nanoribbons and van der Waals heterostructures for functional quantum devices.
Primary supervisor: Dr. Sara Sangtarash
Email: Sara.Sangtarash@warwick.ac.uk
Use the link to explore the project in more detail.
Experimental Fluid Mechanics
I am offering projects in experimental fluid mechanics. The exact project to be worked on will be discussed with any potential candidates interest in the area and taking there interests into account.
Primary supervisor: Professor Peter J. Thomas
Email: P.J.Thomas@warwick.ac.uk
The University of Warwick provides an inclusive working and learning environment, recognising and respecting every individual’s differences. We welcome applications from individuals who identify with any of the protected characteristics defined by the Equality Act 2010.