Join over 500 researchers working with industry and government to address some of the problems facing the world today.
Electronics and computer science (ECS) is the leading university department of its kind in the UK. We were on of the first universities to be named an Academic Centre of Excellence in Cyber Security Education (ACE-CSE) by the UK government.
Our research is organised around research groups and centres. You'll join one of these groups. This means that specialist academics will always be on hand to hear your ideas and offer help and encouragement. With around 250 staff, ECS has unrivalled depth and breadth of expertise.
You'll have the freedom to run your own project and you'll be supported by a team of supervisors. Direct and regular contact with your supervisors will help you develop your scientific insight, and steer you towards creative and original thinking.
Our graduate school provides training on transferable skills, courses on research methodology, and a working framework to help you settle into a disciplined working routine. You'll also have opportunities to travel to international conferences and events to present your work.
ECS holds an annual careers fair that attracts major companies. The majority of our graduates take up roles in the technology industry or develop their research interests further. If you have a great idea our Future Worlds startup accelerator is there to nurture aspiring entrepreneurs through one-to-one support and its network of investors.
This is our standard 3-year research degree. When you apply, you'll choose one of the following:
SustAI is a multidisciplinary and inclusive doctoral training programme. The CDT will provide 70 fully funded PhD studentships over 5 cohorts. SustAI will equip students with state-of-the-art AI technical skills and a deep understanding of how these skills can be applied to address pressing environmental challenges. To register your interest, please sign-up for the newsletter here.
Contribute to the field of research in computer science and software, either in person or through distance by completing a PhD with us.
Contribute to the field of research in computer science and software, either in person or through distance learning, b
A key feature of ECS is that we are truly interdisciplinary. Many of our research groups sit at the interface between electronics and computer science, including cyber security and cyber physical systems. Areas include:
The University of Southampton 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.
Structured studentships are advertised PhD projects with a title, supervisor, remit and funding already in place. These projects have been set up through collaborations with industry, external partners or they may have been provided through one of several centres for doctoral raining which we take part in.
Taking one of our structured studentships will give you access to additional training, conferences and secondments.
Novel crystalline photonic devices offer exciting opportunities for creating efficient lasers and manipulating the properties of light. Pulsed Laser Deposition (PLD) is an extraordinary technique using light to create new materials and devices.
The project will explore new techniques in computer vision to enable AI on the “edge” i.e. within AUVs, as well AI-enabled scheduling on-board the robot.
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.
This project aims to develop an AI-based practical solution for 3D environments understanding from multi-modal (audio/visual) input data and reproducing it in a virtual or augmented reality space allowing real-time 3D interaction with spatial audio adapted to the environment and user locations.
The main research problem in this project will be to explore how AI tools can help domestic end users in their switch to renewable energy, and to do so in a trustworthy manner.
The aim of this project is to develop the next generation of hollow core optical fibres (HCF) using the power of Artificial Intelligence (AI).
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 PhD project tackles the urgent need for robust security solutions in cross-chain environments in Web3, aiming to safeguard the integrity of interconnected blockchain networks.
This PhD project automates cyber-attack attribution using AI and NLP, enhancing defence strategies against evolving cyber threats. Objectives include dynamic attacker identification, a threat intelligence dashboard, and a QA system for real-time analysis. Applicants gain expertise in malware analysis and NLP, driving impactful cybersecurity innovation for proactive threat resilience.
The national grid is increasingly struggling to cope with the increasing renewable energy supply, as well as the increased demand from electric vehicles. To address this challenge, this project will use multi-agent system approaches including mechanism design and MARL to design decentralised systems whereby energy is produced and used locally.
This PhD project aims to develop optical metasurfaces with extreme light manipulation capabilities by employing deep learning-based design methodologies alongside advanced nanofabrication techniques pioneered by our teams at Southampton. These cutting-edge devices will be applied to intelligent sensing applications in complex environments, including those in biomedical fields and consumer electronics.
This PhD project leverages Digital Twin technology for cybersecurity in Critical National Infrastructure, focusing on real-time cyberattack monitoring and Operational Technology security. By creating secure digital replicas of physical systems, the research aims to enhance Critical national infrastructure resilience and offer a proactive defence strategy against potential cyber threats.
Interested in building trustworthy and responsible AI? Then join us at the University of Southampton to incorporate ethics into AI and build models and systems which can act in alignment with the ethical preferences of their users. Test and deploy these across diverse applications like transportation, energy management, disaster response.
This PhD project aims to advance iterative learning control (ILC) by overcoming the limitation of requiring identical references in each trial, a constraint that can be impractical for many real-world applications. By combining optimization, machine learning, and biological insights, this research will develop ILC algorithms that learn faster and adjust to trial-varying tasks.
This PhD project aims to advance iterative learning control (ILC) by eliminating the dependency on analytical models, which are often costly or impractical to obtain. By leveraging data-driven control and optimization methods, this research will develop novel ILC algorithms that achieve high convergence performance directly from data.
With the electrification of transportation happening at breakneck speed for both ground and air vehicles, it is important to be able to measure temperatures of key components. This is particularly important for batteries as these are vital components in any transport system and this project will address this using a novel ultrasonic technique.
As a research project within the Doctoral Centre for Advanced Electrical Power Engineering this thesis will investigate the design of high-power density cables for the next-generation electrified aircraft.
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 will incorporate specific choices of configurations of quantum state preparation gates that use integrability to control the search spaces to be explored.
This project aims to develop advanced technologies and systems that integrate biological sensors, data analytics, and artificial intelligence to monitor, diagnose, and manage health conditions and diseases. These systems are designed to provide real-time, accurate, and personalised information about a person's health status, allowing for timely interventions and better healthcare decision-making.
To trust Deep Learning models in sensitive applications such as autonomous vehicles or healthcare, we need to better understand which information they rely on when making decisions. In this project we set out to create novel tools to solve this crucial step towards AI Safety.
This project explores developing robust machine learning algorithms to detect, regulate, and mitigate risks associated with the use of Artificial Intelligence systems, such as overconfident predictions, bias, time varying distributions and privacy violations.
This PhD project aims to develop machine learning algorithms for the inverse design of metasurfaces, targeting applications in intelligent sensing for complex environments, such as biomedical fields and consumer electronics.
This PhD project explores the application of advanced machine learning on wearable biosignal data, such as heart rate and activity levels, to enhance personalized health monitoring. Focus areas include multimodal data integration, real-time processing, and privacy-preserving techniques for predictive health insights, offering impactful advancements in personalized digital healthcare solutions.
This project addresses malicious energy draining attacks (which significantly increase power consumption of deep learning algorithms) and contributes to energy-efficient artificial Intelligence (AI). You will have opportunities for collaboration in academia and industry, including Cambridge, Microsoft, Nvidia, ARM, and Google DeepMind.
This PhD focuses on developing deep-learning techniques based on multimodal natural language processing (NLP), including large language models (LLMs), audio processing, computer vision (pose estimation, emotion recognition), knowledge graphs or neurosymbolic models in computational social science, analysing discourse in text/audio/video format, including emotional rhetoric analysis, information extraction, and argument mining.
This PhD project involves developing nanoscale optoelectronic devices for next-generation memory and neuromorphic computing. You will explore advanced materials and nanopatterning techniques to create flexible, brain-inspired devices that emulate neural networks, enabling AI in wearables.
This project will develop a novel memristor device using nanoporous materials for the new generation of time and power efficient neuromorphic computing and AI.
This project is focused on how can control systems effectively manage unpredictable nonlinear dynamics in continuous-time systems using real-time sensor data. The main theoretical tool is orthonormal bases of function spaces. This is a project within the Doctoral Centre for Advanced Electrical Power Engineering.
An aging population incurs huge socioeconomic cost due to neurodegenerative diseases, for several of which there is no treatment. This project will address the challenge of interpreting molecular, genetic, and imaging data using machine learning models.
In this project, you will develop new foundations for quantitative verification grounded in the mathematical theory of coalgebras. By studying quantitative logics, their expressiveness and their associated model checking problems, you will lay the groundwork for verification tools that are more widely applicable and more expressive than existing ones.
We are looking for an exceptional candidate to join our team to develop a novel technique to dope transition metal dichalcogenides and investigate their commercial potential by working with our industrial partners, Intel, Graphenea and Grolltex.
The main goal is to improve the state-of-the-art mechanisms for the allocation of scare resources from different, and not always compatible, perspectives of efficiency, fairness and resilience. Multi-agent systems and machine learning techniques will be used to develop better and more sustainable mechanisms.
In this project, we will carry out a detailed threat analysis of quantum-computer attacks on cyber-physical systems, which takes into consideration system configurations, data criticality, and the likelihood of the attack.
This PhD project aims to develop advanced soft robotic systems with integrated sensing, on-demand therapy, and AI-driven closed-loop control. This interdisciplinary research opportunity merges medical robotics, bioelectronics, and wearable technology for transformative healthcare applications. Ideal for innovators in biomedical engineering, robotics, or flexible electronics.
We are pushing the boundaries of quantum technology by exploring both the theoretical and practical potentials of space-time-modulated superconducting surfaces and their applications in quantum processors and computers. This pioneering approach holds the promise to transform next-generation superconducting quantum technologies, while actively engaging industrial partners for impactful real-world applications.
Concerns about the environmental impact of electronics are increasing, and the IoT will deploy billions of devices. Choices made about power supplies, edge AI algorithms, and processors influence their use of materials, carbon footprint, and longevity. In this PhD, you will explore design-time approaches to enhance sustainability of devices.
This PhD project explores how artificial agents can autonomously develop symbolic communication systems, resembling human alphabets or logograms, purely through interaction. Building on previous studies in sketch-based communication, the project investigates how agents might evolve compact, meaningful symbols, potentially mirroring early human writing systems, that enable efficient exchange of information.
Time series machine learning is a rapidly evolving field of artificial intelligence research. This project involves researching new algorithms for time series classification, helping develop the open-source aeon python toolkit, and collaborating with international partners to apply these algorithms to applications in health technology and human activity recognition.
The predictive power of deep learning models offers widespread promise, but they are hard to interpret. Their predictions do not have associated measures of uncertainty. To address these shortcomings, this project will develop measures to characterise the reliability of deep learning models based on prior work on probabilistic model compression
Internet-connected devices, such as mobile or IoT devices, are now widely used in elderly care for monitoring and tracking. This project aims to explore the security, privacy, and usability issues that older adults and their caregivers face throughout the life cycle of these Internet-connected devices.
The aim of this project is to design a human-in-the-loop aerial swarm system to detect and suppress wildfires.
We offer a wide range of fully funded studentships. We run several of our PhD studentships in partnership with doctoral training centres, meaning you'll benefit from enhanced training and guaranteed funding.
These studentships:
Doctoral training centres offer fully funded studentships which include:
In association with the UK joining the EU Horizon Programme, the University of Southampton will be introducing and applying an EU fee waiver for students joining us from EU and Horizon associated countries. This means that PGR students joining us from 2024-25 will pay the same fees as UK PGR students.
See here for full information terms and conditions
We offer scholarships and teaching bursaries ourselves. Your potential supervisor can guide you on what is available.
If you’re an international student you may be able to apply for a scholarship from your country.
Find out more about scholarships
Once you've found a supervisor, they can help you with potential funding sources. We offer match funding in some cases.
You'll need to state how you intend to pay for your tuition fees when you submit your application.
Find out more about funding your PhD
You may be able to fund your postgraduate research with funding from your current employer or from industry.
You can borrow up to £29,390 for a PhD starting on or after 1 August 2024. Doctoral loans are not means tested and you can decide how much you want to borrow.
Find out about PhD loans on GOV.UK
You may be able to win funding from one or more charities to help fund your PhD.
We charge tuition fees for every year of study. If you’re applying for a fully funded project, your fees will be paid for you.
EU Fee Waiver: If your country is part of the Horizon Europe Programme, you will pay the same fees as UK students.
Find out if your country is part of the Horizon Europe programme
2023 to 2024 entry:
| Subject | UK and Horizon programme applicants | International fees |
|---|---|---|
| Computer science full time | £4,712 | £25,500 |
| Computer science part time | £2,356 | £12,750 |
| Electronics and electrical engineering full time | £4,712 | £25,500 |
| Electronics and electrical engineering part time | £2,356 | £12,750 |
2024 to 2025 entry:
| Subject | UK and Horizon programme applicants | International fees |
|---|---|---|
| Computer science full time | £4,786 | £26,100 |
| Computer science part time | £2,393 | £13,050 |
| Electronics and electrical engineering full time | £4,786 | £26,100 |
| Electronics and electrical engineering part time | £2,393 | £13,050 |
2025 to 2026 entry:
| Subject | UK and Horizon programme applicants | International fees |
|---|---|---|
| Computer science full time | To be confirmed Spring 2025 | £26,700 |
| Computer science part time | To be confirmed Spring 2025 | £13,350 |
| Electronics and electrical engineering full time | To be confirmed Spring 2025 | £26,700 |
| Electronics and electrical engineering part time | To be confirmed Spring 2025 | £13,350 |
You're eligible for a 10% alumni discount on a self-funded PhD if you're a current student or graduate from the University of Southampton.
Our research takes place in a multidisciplinary, collaborative environment, organised across globally important research groups and national research centres.
We offer 2 doctoral routes:
If you choose our standard research PhD, decide whether to apply to an advertised research project or create your own proposal.
Whichever programme you choose, you'll need to identify a potential supervisor. Therefore it's a good idea to email supervisors working within your field of interest to discuss PhD projects. It's best to do this well ahead of the application deadline.
You’ll find supervisors’ contact details listed with the advertised project, or you can search for supervisors in the staff directory.
As part of your online application, you’ll need to send us:
The application process is the same whether you're applying for a funded project, or have created a research proposal.
You should have a 2:1 honours undergraduate degree or equivalent qualification in a relevant discipline.
If English is not your first language, you'll need an IELTS minimum level of 6.5 with a 6.0 in writing, reading, speaking and listening.
If you are applying for the SustAI iPhD. you'll need an IELTS minimum level of 6.5 with a 6.0 in writing, reading, speaking and listening.
Your awarded certificate needs to be dated within the last 2 years.
If you need further English language tuition before starting your degree, you can apply for one of our pre-sessional English language courses.
Check the specific entry requirements listed on the project you’re interested in before you apply.
Research degrees have a minimum and maximum duration, known as the candidature. Your candidature ends when you submit your thesis.
Most candidatures are longer than the minimum period.
| Degree type | Full time | Part time |
| Computer science PhD | 2 to 4 years | 3 to 7 years |
| Electronics and electrical engineering PhD | 2 to 4 years | 3 to 7 years |
