Join over 500 PhD students in one of the largest and most diverse engineering, environmental science and audiology faculties in the UK. We develop solutions in areas including sustainable energy, green transport, resource efficiency and resilient infrastructure.
Engineering at the University of BOB体育登录网址_欧宝体育官网平台-APP|下载 has subjects ranked within the global top 100 and the UK’s top ten in the QS World University Rankings by Subject 2022.
You'll be supported by a team of academic supervisors who'll be on hand to guide your research and provide advice. Working alongside our world-class team of researchers means you'll be working on cutting-edge research and pioneering solutions.
We'll provide you with the grounding you need to become a successful researcher. You'll benefit from both technical and personal training. You'll also be able to develop your skills further through placements in industry, mentoring, attending conferences and presenting your work.
Most of our research projects have strong links with industry so you'll be able to conduct experiments at a variety of facilities to ensure your research has real world impact.
If you've completed your undergraduate and masters degrees and want to continue in the same field, then the standard research PhD is probably the right option.
Contribute to the field of research in computer science and software, either in person or through distance learning, by completing a PhD with us.
BOB体育登录网址_欧宝体育官网平台-APP|下载 research areas include:
The University of BOB体育登录网址_欧宝体育官网平台-APP|下载 is pleased to announce that PGR students from EU and Horizon associated countries joining us in 2024-25 will pay the same as UK PGRs for their PhD.
You can either apply for a structured studentship or propose your own PhD idea.
Taking a structured studentship will give you access to additional training, conferences and secondments. Full studentships typically cover tuition fees (at EU/UK level) and provide a tax-free bursary which varies depending on the programme.
We offer our structured studentships in partnership with our Centres of Doctoral Training (CDT).
This project focuses on developing a cutting-edge quantum sensing platform based on Photonic Integrated Circuits (PICs) and 2D materials such as Transition Metal Dichalcogenides (TMDCs) for ultra-sensitive point-of-care diagnostics and environmental monitoring.
Delicate, high-value objects such as museum artefacts or medical goods warrant bespoke packaging solutions for protection against shock and vibration damage during transit. This project will develop the capability to design and 3D print packaging from metamaterials that derive their mechanical properties in-part from the geometry of their porous architecture.
This PhD project will use Resolvent Analysis (RA) to tackle turbulent flow modelling without the need for expensive, scale-resolving simulations. By developing algorithms that dynamically balance RA structures, the project aims to synthesize an approximate turbulent velocity field, enabling detailed yet computationally efficient analysis of complex flows.
We’re looking for a passionate PhD student to join our team and push the boundaries of what’s possible with Pulsed Laser Deposition (PLD).
Traditional circuit theory, grounded in transfer functions and state-space models, fall short at addressing the complexities of modern, bidirectional power networks. This project investigates data-driven control methodologies tailored for active networks, with a particular focus on coordinated control strategies, distributed controllers, and their practical implementation on power converter devices.
This project will use device simulations combined with transient electronic and optoelectronic characterisation techniques to unambiguously identify the resistive switching mechanisms underlying memristors based on a wide variety of materials systems including perovskites and titanium-based compounds.
Are you ready to embark on a journey of otherworldly research? Do you want to be part of the space revolution that is pushing the frontiers of humankind and helping us understand our world and our climate? If so, then join the world-leading Hollow Core Fibre group at the University of BOB体育登录网址_欧宝体育官网平台-APP|下载 and develop advanced sensors that are enabling the next generation of space missions.
This project focuses on understanding and modelling the vibroacoustic mechanisms of early British pianos. The goal is to create virtual replicas of these historical instruments, with an emphasis on the design of hammers, strings, and soundboards, to preserve and appreciate their original sounds.
This PhD will develop new AI for clearer speech, focusing on helping those with hearing loss understand conversations better, especially in noisy places. The goal is to improve hearing aids and assistive tech using cutting-edge Transformer networks.
This innovative project aims to advance marine sensing technologies by expanding the range of analytes and pollutants that can be detected using a novel surface plasmon resonance technique.
This project will develop an integrated membrane electrochemical system (MES) for efficient lithium separation and CO? capture. By combining advanced membrane materials development with electrochemical process design and optimisation, it aims to deliver a transformative solution for sustainable resource recovery and carbon management.
This project is focused on transforming respiratory care at the bedside to develop a user-friendly, palmtop spectrometer that brings rapid bedside biomarker diagnosis within easy reach for clinicians.
This is a predominantly experimental project that makes use of the strong facilities of the telecommunication systems laboratory of the ORC.
AI Safety in the health setting. Advancements in AI lead to clinical uses of AI systems for the triaging and care suggestions for patients. AI Safety in the clinical setting has a diverse range of stakeholders, regulatory requirements and needs.
Robust design is crucial for ensuring the durability and reliability of aerospace components throughout their entire life cycle, given the variations that arise from geometry, material properties, and loads during long-term operation.
The marine and maritime sectors face an urgent need for green energy solutions and effective decarbonization strategies. BOB体育登录网址_欧宝体育官网平台-APP|下载 project focuses on the development of AI-enhanced numerical tools to help address these challenges.
Are you interested in exploring cardiovascular biomechanics and machine learning in biomedical applications? Be part of a research that merges AI-based medical image processing and multiphysics cardiovascular modelling towards a better understanding of heart diseases and developing patient-specific treatment options.
This project focuses on railway noise and vibration. By integrating computational modelling, experimental measurements, and AI-driven insights, the research aims to develop predictive models for noise reduction and sustainable railway development.
This PhD project explores the use of Physics-Informed Neural Networks (PINNs) to solve environmental flow problems, including the 2D Shallow Water Equations. Combining advanced artificial intelligence (AI) with fluid mechanics, the research aims to develop fast, accurate, and robust simulations for applications like flood modelling and water management.
Explore the space where physics-based modelling and artificial intelligence meet. Join this project on ultrasonic non-destructive characterisation of complex materials. This project will explore various artificial intelligence tools combined with ultrasonic experiments, physics-based simulation and inversion to develop reliable tools for safety-critical assets.
The aim of this project is to establish a new class of sensing system that is capable of mapping strain distribution at thousands of points using a single strand of optical fibre thinner than a human hair.
This project will investigate how humans perceive object properties and their environment through sound, focusing on single impact sounds. The project will explore implications for audio-visual integration, gamification, speech perception, and auditory scene analysis. It will also examine the fundamental mechanisms of auditory perception and how we interpret simple sounds to understand our surroundings.
In this project you will have the opportunity to develop and test novel methodologies to extract ship hydrodynamic characteristics from a focused set of tests. The ambition is to disrupt conventional approaches, by exploring novel hydrodynamic test and evaluation practices.
This project aims to study and identify the beneficial effects of using bio-inspired geometry on aerofoils, enhancing aerodynamic efficiency and reducing the noise generated from non-equilibrium turbulent boundary layers.
We are seeking a motivated PhD candidate to develop bio-inspired smart skin that emulates the remarkable sensory abilities of human skin. This technology will transform prosthetics and humanoid robotics, allowing these systems to engage with their environments with exceptional sensitivity, safety, and adaptability. Your work will help restore sensory perception for individuals with sensory loss and enhance the tactile responsiveness of humanoid robots for safer and more intuitive human-robot interactions.
This project focuses on the development of novel bioinspired soft robots based on smart materials for complex locomotion and manipulation in natural environments.
Tidal Turbines (underwater wind turbines) are able to operate close together and this can increase power capture. To get it to work well we need to understand many different aspects of device design and operating environment. Building on existing work you will experimentally and numerically investigate ways to boost performance.
This project will investigate across-scale physical processes in urban areas, with a focus ranging from the metre to kilometre scales.
This PhD project focuses on characterizing and predicting noise in short intake ducted propeller systems for eVTOL aircraft, critical for Urban Air Mobility noise reduction. Using advanced techniques like Particle Image Velocimetry (PIV) and acoustic measurements, this research will inform models and explore acoustic liners to reduce noise emissions.
This project focuses on experimentally characterizing and predicting noise from tip vortex-blade interactions in eVTOL aircraft, addressing a key challenge in reducing noise for urban air mobility. Using advanced techniques like Particle Image Velocimetry (PIV) and hotwire measurements, this study will inform noise reduction strategies in next-generation urban air mobility systems.
Fully funded PhD investigating novel design methods to improve submerged infrastructure resilience against currents and waves. Utilize world-class hydraulic labs and supercomputing facilities to develop sustainable, carbon-efficient solutions.
As battery pack is an environmentally and financially expensive subsystem in an Electric Vehicle (EV), a robust Battery Management System (BMS) is crucial for EV durability. This project aims to pursue research on cloud based adaptive BMS for improving the battery pack lifetime, thereby assisting market adoption of EVs.
Are you excited about the future of high-energy laser systems? Cryogenically cooled lasers are paving the way for next-gen high-power applications. We’re looking for a passionate PhD student to help us develop cutting-edge, compact “turn-key” solid-state lasers that operate in the visible and UV wavelength bands.
This project will use computational modelling in combination with 3D multiscale multimodal imaging to improve our understanding of placental evolution, in close collaboration between Engineering and Medicine.
The objective of this project is to integrate quantum communication into emerging wireless networks, paving the way for a global quantum network in time for 6G.
This project will explore how we can deploy unprecedented levels of renewable energy into the electric grid. It will focus on the controller design of pants like solar and wind to ensure stable and reliable power system. This research is part of the Doctoral Centre for Advanced Electrical Power Engineering.
Scaffolds are important physical substrates for cell attachment, proliferation and differentiation, ultimately leading to the regeneration of tissues. This research aims to develop a novel multi-material functional gradient scaffold that mimics the natural bone and cartilage structure, promoting the regeneration of both, particularly the transition zone between the two.
This project aims to develop a high-performance, low-cost propulsion system for CubeSats, enhancing manoeuvrability and mission longevity. Building on the All-Printed Propulsion System (ALPS) concept, this research will explore plasma acceleration using electric and magnetic fields, enabling a dual-stage propulsion system for improved thrust and efficiency in micro- and nanosatellite applications.
This exciting PhD project focuses on advancing single-wavelength intracavity absorption spectroscopy for marine sensing.
Respiratory diseases develop progressively. However, current monitoring methods are unsuitable for long-term continuous monitoring. Near-infrared spectroscopy (NIRS) uses light to interrogate the optical properties of tissue. This project aims to develop a wearable system for long-term respiration monitoring using NIRS powered by artificial intelligence (AI) to aid in analysis.
This project aims to develop innovative miniature ultrasonic devices specifically designed for bone surgery. It aims to advance the current design by introducing innovative configurations, incorporating novel structures in miniaturized devices, and integrating them with surgical robotics to enhance precision and improve clinical outcomes.
This project will employ advanced engineering methods, including data mining, signal processing, and machine learning based on our advanced wearable sensors, to detect gait disorders.This interdisciplinary research aims to deliver critical outcomes that will underpin future healthcare monitoring systems and its potential integration of the Internet of Medical Things.
This project aims to develop advanced digital twin technology for space object re-entry monitoring, addressing multiphysics coupling and hybrid uncertainties. The project focuses on uncertainty quantification, robust model updating, and real-time data integration to improve re-entry prediction accuracy.
In this project you will be working with a large research team in BOB体育登录网址_欧宝体育官网平台-APP|下载 and with our colleagues from the University of Texas, USA on heterogeneous integration of silicon photonics devices with barium titanate (BaTiO3 or BTO), a material that has one of the largest modulation effects, using mass manufacturable techniques and new design ideas.
Efficient anchor design methods are urgently needed for upscaling offshore renewable energy infrastructure and unlocking farm-scale floating wind developments. During this PhD project, you will learn about whole-life anchor design and seabed response, to then lead the way in developing these into new design approaches for anchoring systems.
The main goal of this project is to investigate and design novel electrodes for minimally invasive brain sensing.
This PhD project will focus on developing cutting-edge optical fibre amplifier technologies designed to reduce power use, lower the cost-per-bit, and enhance overall data capacity.
This project aims to develop an intelligent engineering system to monitor and improve quality of chest compressions for cardiopulmonary resuscitation (CPR), including in out of hospital settings.
Autonomous underwater vehicles (AUVs) are playing an increasing role in studying our oceans. While they can be equipped with a range of physical sensors, options for chemical monitoring are limited for smaller AUVs. This project looks to address this by developing new AUV systems for measuring ocean chemistry.
This project aims to develop, fabricate, and test new technology for studying sediments that will enable scientists to gain new insights into our coastal environment.
This PhD project aims to develop low-carbon, high-performance cementitious materials to combat marine corrosion and reduce global CO? emissions. Using advanced material characterisation techniques, this project explores microstructure evolution and long-term durability for sustainable ocean infrastructure.
Nanobubbles, characterised by their unique features, present a compelling opportunity to improve biological treatment process performance and efficiency. This project will investigate the application of nanobubbles in biological waste treatment and their potential for retrofitting existing systems.
Would you like to work with state-of-the-art hardware and innovative software, using your skills to improve world-leading imaging techniques?microCT scanning is a key technology in non-destructive imaging across many applications. You will extend the capabilities of existing microCT scanners expanding their capabilities to improve scientific understanding.
This project studies nonreciprocal entanglement between frequency-distinct superconducting qubits, enabled by spatiotemporal superconducting metasurfaces.
Composite materials are at the forefront of airframe technologies successfully providing reliable and high performance aerospace structures. A key barrier to greater deployment of next generation composites for new and novel vehicle concepts is the time and cost associated with certification of new designs.
This PhD project will investigate the electrical, thermal and economic modelling of a range of electrical energy storage types (e.g. lithium-ion and lead-acid batteries, flow cells and fuel cells), with a view to further investigation of the potential to directly hybridise these energy stores.
The aim of this research project is to investigate how airfoil self-noise is generated through the interaction between an airfoil blade and the turbulent boundary layers that form over it, and how these structures can be manipulated for flow and noise control.
This project aims to investigate fluid-structure interaction using travelling waves for propulsion and micro-pumping applications. It combines structural dynamics, fluid mechanics, and advanced numerical modelling to develop efficient, bio-inspired motion strategies for underwater vehicles, biomedical devices, and microfluidic systems.
This project will focus on investigation of advanced mode-locked techniques to realize high-performance ultrafast fibre lasers.
In this PhD studentship, you will further develop novel composite material ARF (CM-ARF) technology, spanning the multidisciplinary remit between cleanroom based, 2D materials fibre integration technology for the highly innovative CM-ARF platform, with applications in active photon management and light processing functions.
As a research project within the Doctoral Centre for Advanced Electrical Power Engineering this project will investigate the impact of heterogeneous burial environments on the power flow capacity of high voltage submarine cables.
This PhD project, in association with BAE Systems, seeks to reveal and investigate novel solutions to deliver significant improvements in overall energy efficiency in maritime transport.
This project investigates bio-inspired fluid-structure interactions to improve wing resilience under unsteady conditions. By studying how insects adapt to dynamic environments, such as turbulence and surface interactions, we aim to develop innovative strategies for enhancing wing performance. The goal is to apply these insights to advanced, adaptive flight systems.
This project aims to develop the next-generation photonic integrated platform operating across the UV-NIR spectrum for quantum applications.
The goal of this project is to create a predictive sensing methodology, leveraging AI-driven analytics to provide detailed temporal and spatial flow characteristics.
This PhD project is about pushing the boundaries in manufacturing, and making lasers become autonomous decision-makers, guiding us into a future of faster, cleaner, and more precise production processes.
This PhD project explores an eco-friendly “flash carbide” coating for extreme wear environments in aircraft landing gear. Through advanced tribological testing and materials damage modeling, it will benchmark this new High Velocity Air Fuel-deposited coating against conventional High Velocity Oxy Fuel alternatives. The findings would benefit the aerospace industry with cost-effective, sustainable, and high-performance coating solutions.
This project investigates the environmental impact of spacecraft re-entry, focusing on material ablation and its effects on ozone chemistry and Earth’s radiative balance. Using high-fidelity computational models, molecular dynamics, and atmospheric simulations, this research will enhance sustainability in space activities by assessing the long-term consequences of satellite disposal practices.
This project will investigate how adding metal plasma can improve the performance of air-breathing plasma thrusters, with a focus on developing an optimized neutralizer-free design for Very Low Earth Orbit environments.
Revolutionising the semiconductor industry with next generation 2D materials and devices.Moore’s Law is currently being challenged with Nvidia CEO recently claiming it is over. The scaling of transistors cannot continue due to physical limitations of silicon posing a threat to the sustainable evolution of new technologies.
The aim of the project is to use a laser-based direct-writing technique developed and patented by our group to pattern microfluidic devices in paper for the creation of the diagnostic sensors or tests.
You will design control policies for autonomous systems combining control, optimization, and machine learning tools. The challenges include limited computing resources to run for example complex neural networks models, or limited communication resources for example in networks of robots, and the safety and robustness analysis of the learned policies.
This project will develop machine learning (ML) techniques for processing acoustic data from sensor arrays, allowing the enhancement of signals and localization of sound sources. While ML has been used for single sensors, this project will create new methodologies for processing data from multiple sensors, improving underwater acoustic analysis.
This PhD project advances deep learning for turbulence modeling in combustion. Using CNNs and GANs, it tackles challenges in data demands and generalization. The goal is to develop predictive models for hydrogen-based and carbon-neutral fuels, guiding sustainable energy design. Key tasks include model optimization, integration, and Exascale scalability.
This project will develop the core components of superconducting and atom/ion trap quantum systems using ultra-precision diamond machining. You will work with leaders in the field (academia and industry) to create vacuum systems with integrated photonics and electrical functionality.
In this project we will develop hollow-core optical fibres (HCFs) for mid-infrared laser delivery. HCFs offer a radically new solution for laser delivery as they guide light in a gas-filled core, instead of the glass in conventional optical fibres.
The project focuses on understanding cerebral blood flow and its physiological control, to improve diagnosis and treatment of brain injuries. The project will adopt a control and system identification approach, and will benefit from the use of real data, clinical collaborations, and links with the international research network CARNet.
This project will explore gust-wing interactions in curvilinear flows, focusing on vertical axis wind turbines (VAWTs). It offers a unique opportunity to develop expertise in computational fluid dynamics (CFD), data-driven modelling, and experimental aerodynamics while addressing a critical challenge in renewable energy, such as gust-wing interactions in curvilinear flows.
Soil is one of the most complex and important self-assembling organo-mineral composites in the world. All human food supply, ecosystem and infrastructure services depend on soil. Movements of water into, within and out of soil are especially important.
This project aims to identify the role and mechanism by which hard phase support galling resistance to support the production of a microstructural model which allows the role of the hard phase to be investigated under a range of operating loads informed by experiments.
This innovative project will enable the miniaturization of Lab-on-Chip (LOC) systems, making them compatible with smaller, more compact Autonomous Underwater Vehicles (AUVs) for real-time, in situ environmental monitoring.
We are looking for an enthusiastic PhD candidate to join our research team for a project focused on developing photonic integrated circuits for UV-green wavelengths.
This project aims to develop advanced nonlinear damping mechanisms for space exploration and extraterrestrial colonisation. Combining numerical modelling, experiments, and compliant mechanisms, this research tackles regolith interactions and extreme conditions to improve structural resilience.
This project aims to investigate nonlinear dynamic behaviour in space structures, focusing on light, flexible systems in extreme environments. It combines numerical modelling, analytical methods, and experimental validation to enhance structural resilience for space exploration and extraterrestrial colonisation in collaboration with the European Space Agency (ESA).
This project seeks to develop novel fluidic topology optimisation approaches for gas turbine component design by leveraging cutting edge machine and deep learning methods alongside computational fluid dynamics, ultimately aiming to revolutionise the solution of aerodynamic design problems.
This project will develop novel techniques to enhance the physical layer performance of 5G non-terrestrial networks. In particular, Multiple Input Multiple Output (MIMO) techniques for exploiting inter-beam interference and for user-specific beamforming can be used for enhancing capacity and coverage.
This PhD project develops optimised surface topographies for drag reduction in turbulent flows. Using Reynolds-Averaged Navier-Stokes simulations and linear input-output analysis, it aims to design passive surfaces that influence turbulent scales for efficient drag control. Ideal for candidates with expertise in fluid dynamics, CFD, and mathematical optimisation.
Magnetometers are crucial in aerospace, geological mapping, and drone technology. BOB体育登录网址_欧宝体育官网平台-APP|下载 innovative project leverages distributed quantum sensing, implemented on an array of optomechanical metasurfaces, to create room-temperature, chip-scale remote magnetometers with high signal-to-noise sensing capabilities in complex environments.
We’re on the lookout for a passionate and innovative PhD student to push the boundaries of on-chip sources in the 2-micron wavelength window.
This multifaceted project targets the development of an all-in-one photoreactor described using multi- phase chemical models to incorporate the kinetics of photocatalysts, reactant flow and photon behaviour.
In this project, you will develop and evaluate novel quantum machine learning approaches to solve large scale inverse problems using near term quantum computing systems.
This project aims to develop a criticality ranking system for power grid assets using data-driven approaches. By applying machine learning and statistical models, it prioritizes high-risk assets, enabling proactive decisions, optimised resource allocation, enhanced maintenance efficiency, and improved grid reliability.
This project explores quantum computing to enhance large-scale stochastic optimisation for energy system planning, addressing uncertainty in renewables. By integrating quantum and classical methods, it aims to solve large-scale models, advancing methodologies and supporting the energy transition.
This project aims to investigate the bioelectric heterogeneity of colorectal cancer (CRC) and its correlation with bowel diseases and drug response, using quantum diamond microscopy (QDM).
The aim of the project is to develop a novel platform technology for quantum reservoir computing, a promising approach for quantum neural networks where quantum information can be used as data in machine learning algorithms.
This project investigates the development of quantum algorithms to enable large-scale topology optimisation in aerospace. The goal is to overcome computational barriers in designing energy-efficient, sustainable aircraft configurations by leveraging quantum methods, advancing beyond the limits of conventional optimisation for practical aerospace applications.
This project aims to revolutionise diagnostics with a quantum-enhanced mid-IR sensing platform for quick, easy and non-invasive detection of pollutants and disease markers. By integrating advanced materials, it will enable ultra-sensitive, real-time environmental and health monitoring, offering a powerful tool for early disease detection and improved pollutant tracking.
When gas flows from a coaxial nozzle surrounded by a liquid, it forms reproducible liquid shells useful in industries needing hollow spheres, such as pharmaceuticals and 3D printing. This project aims to understand and optimize production rates, reproducibility based on nozzle design and operating parameters.
This project will study how overhead line equipment in existing rail networks ages and deteriorates over time when exposed to stronger electric fields and more extreme weather conditions.
Emerging micropollutants, including pharmaceutical residues, personal care products, and industrial chemicals, contaminate global water sources and pose health risks. This project will identify key microorganisms capable of breaking down toxic, persistent organic compounds and develop an effective biofilm with specialized strains to enhance micropollutant removal in bioreactors.
In this project you will explore novel wave energy harvesting systems for maritime robotic systems, such as Autonomous Surface and Underwater Vehicles (ASVs and AUVs).
You will develop a novel predictive model for the 'silent' installation of open-ended piles for offshore wind turbine foundations, through advanced physical and numerical modelling. You will improve the fundamental understanding of pile installation, while developing practical tools for the offshore industry, accelerating the path to a carbon-neutral world.
This project explores how Large Language Models (LLMs) enhance lifelong robot learning by incrementally acquiring and refining visuomotor skills. It investigates leveraging textual and spatio-temporal data to improve skill adaptation while addressing challenges in continual learning. The methods will be tested in household environments for real-world, open-ended robotic learning scenarios.
This project develops wearable sensors for continuous respiratory rate monitoring. Using thermoelectric materials, e-textile techniques, and micro/nanofabrication, researchers will create flexible, self-powered sensors integrated into wearable devices for respiratory rate monitoring. Work includes material optimisation, sensor design, circuit integration, and breathing rate testing.
MXenes are a promising new family of nanomaterials. They have unique properties and show great promise in many applications fundamental to the net-zero transition (e.g. gas storage, energy storage). This project aims to develop environmentally-friendly, safe, and scalable methods to enable large-scale manufacture of MXenes to meet future industrial needs.
This project aims to develop advanced flexible materials used as dielectric elastomer transducers (DET) in energy harvesting applications. It offers a unique opportunity to drive progress in flexible energy-harvesting technologies and to address contemporary challenges associated with expanding technologies and innovative applications.
This project will explore the combination of Stacked Intelligent Metasurfaces (SIM) and Orthogonal Time Frequency Space (OTFS) in the next-generation Space-Air-Ground Integrated Network (SAGIN).
This project develops advanced and sustainable polymer materials for power electronic inverters in wind energy systems. By combining nanocomposites, cross-linked networks, and bio-based polymers, it aims to enhance thermal, electrical, and mechanical performance, supporting the creation of more reliable, efficient, and environmentally friendly renewable energy infrastructure.
This project will consider a complex set of plasma chemical reactions and physical processes taking place in wet, low pressure air discharges and the noise as well as an erosion associated with corona discharges in electric power equipment.
In this project you will be working on the design and fabrication of silicon photonics circuits that operate in the mid-infrared wavelength region where the drugs have distinct absorption fingerprints.
The aim of this project is to design, develop, and translate 3D nanoscale metamaterials for real-world applications. In this work, nanoscale particles can be assembled into macroscopic structures, creating a new class of materials where the desired properties are enhanced and scaled to a device level.
This project aims to validate the hypothesis that ultrasonic surgical tools can both limit cell damage at the site of cutting and stimulate tissue healing in regions remote from the surgical tip. This is achieved using ultra-high speed imaging based organotypic and hydrogel models for ultrasound-induced effects on bone and soft tissue.
In this project, you will design, fabricate, and test atom and ion trap systems while working with experimentalists to demonstrate quantum sensing and computing.
The aim of this project is to provide a solution for intra data centre communications which is sustainable, and uses minimal power.
This PhD project will develop advanced ultrasonic array techniques for hydrogen leak detection, localisation and characterisation in complex, noisy environments. Combining mathematical modelling and physics-informed signal processing with AI-driven methods (including PINNs), the research aims to enhance robust, cost-effective leak detection with industrial applications on complex sites.