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.
This PhD project is part of a cutting-edge research initiative aimed at developing transformative AI solutions for healthcare by leveraging big data to address key challenges in causal inference, continual learning, and digital twin technology.
In this PhD studentship, the candidate will contribute to the development of a facile, low cost system exploiting direct laser printing of 2D semiconductor based nanodevices.
This project aims to develop AI-driven, metal-based smart antimicrobials targeting gastrointestinal infections and antimicrobial resistance. You will use cutting-edge AI drug design and microfluidic organ-on-a-chip technology for rapid, animal-free drug screening.
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.
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 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.
In this project you will be working with a large research team in Southampton 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.
The aim of this PhD project is to explain the behaviour of a swarm using generative imitation learning.
Flexible electronics are transforming modern technology, enabling lightweight, bendable, and wearable devices that integrate seamlessly into everyday life. From healthcare to smart packaging, flexible electronics provide novel functionalities that rigid counterparts cannot achieve. This project aims to develop highly reliable, durable, and high-speed non-volatile memory on flexible substrates.
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.
Hypoxic-ischaemic encephalopathy (HIE) affects babies' brains during the childbirth due to shortages of oxygen. Using computer vision and machine learning techniques, HIE disease is diagnosed much earlier than two years which is the current normal practice in hospitals. As a result of HIE early detection, then early interventions can be applied to improve the babies health.
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 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 project aims to develop machine learning (ML) techniques for processing data collected from an array of hydrophones (underwater microphones). While our team and other international groups have harnessed ML's capabilities for single hydrophone data analysis, there has been limited exploration of the optimal approach for combining information across multiple hydrophones.
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.
A novel nano-opto-electro-mechanical (NOEM) tunable SiC entangled photon source will be developed for future on-chip quantum photonic circuits technology. Design optimisation, device fabrication and single photon measurements are planned to prove the working principle and tunability of the device.
Enabling integrated and free space photonics with advanced reprogrammable materials. The current increase in data generation is expected to reach unsustainable rates by the end of the decade. This has a strong impact on the environment and therefore new solutions are sought after.
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 PhD project will develop a new sensor technology to diagnose bacterial infections rapidly.
This project aims to develop cutting-edge on-device continual learning for resource-constrained robots. It tackles the stability-plasticity dilemma, enabling robots to learn multiple tasks efficiently while retaining prior knowledge.
This project will investigate a novel nano-opto-electro-mechanical (NOEM) qubit that has been realised on a nanoscale suspended beam, controlled electrically and read out via optical interaction.
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.
This PhD project will research how advanced system-technology co-optimisation (STCO) can be harnessed to enhance the efficiency and sustainability of inference, exploring full-stack co-design including the AI model itself.
This project aims to pioneer advancements in the efficiency of Generative AI Models (GenAI), focusing on achieving lower latencies and smaller model sizes without compromising performance.
This project explores how quantum techniques can reduce communication complexity in distributed systems. It involves studying classical and random communication complexity theories, and applying quantum methods like entanglement and superposition.
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.
With modern computing set to consume around 20% of global electricity by 2030 due to the rise of AI, energy-efficient computing hardware is urgently needed. This project aims to develop electronic and optoelectronic memory devices using ultra-thin layered two-dimensional materials.
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.
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 |
