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.
In this project, several PhD students are working on a pipeline for modelling and rendering of the full environment including 3D geometry, semantic objects and material attributes from multi-modal inputs such as video, audio and text.
Dive into the fascinating world of quantum computing by developing new algorithms for molecular simulations and running your algorithms on actual quantum hardware. Your interest and background shapes the project with a focus on quantum chemistry inspired method development, algorithms enabling ultrafast dynamics, or error mitigation schemes.
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.
The aim of this project is to develop the next generation of hollow core optical fibres (HCF) using the power of Artificial Intelligence (AI).
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.
The main aim of this research project is to develop active noise and vibration control systems for large-scale industrial installations, that overcome challenges of practical system integration through intelligent algorithm design.
Our objective is to develop Nuclear Magnetic Resonance spectroscopy to make it capable of detecting individual quantum spins. This goal will be achieved by developing magnetic lenses to amplify the signal from and out of the spin-hosting materials.
Massively parallel compute architectures, like Graphics Processing Units (GPUs) and Field-Programmable Gate Arrays (FPGAs), are becoming an integral part of the high-performance computing ecosystem. This project is about effective mapping of large parallel problems onto these architectures, improving the optimised performance of numerical simulations and artificial intelligence. You will access leading supercomputer resources to achieve this.
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 main goal of this project is to investigate and design novel electrodes for minimally invasive brain sensing.
This project studies nonreciprocal entanglement between frequency-distinct superconducting qubits, enabled by spatiotemporal superconducting metasurfaces.
In this project, you will apply machine-learning and data science techniques to discover anomalies in vast data sets of radio pulsar observations, use these to understand how neutron stars evolve over their lifetimes, and advance our ability to use pulsars as tools to push the boundaries of modern physics.
The field of computing is facing a conundrum caused by a clash in two opposing trends: on the one hand, the growth and proliferation of machine learning (ML) in software, and on the other hand, ever-growing concerns that, with ML models being a black-box technology, the safety, security and explainability of software that uses ML diminish.
New femtosecond fibre laser-based ultrafast pulse sources and novel hollow-core optical fibres have the potential to produce brighter and shorter-wavelength X-ray pulses. This project will investigate theoretically and numerically how these new sources can be developed and optimised, in parallel with the experimental work in our labs.
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.
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.
The Web Science Institute (WSI) at the University of Southampton is offering PhD studentships for multidisciplinary doctoral research with a particular focus on Human-Centred Artificial Intelligence (AI).
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.
The ability to design new more efficient down conversion systems will be of paramount importance for the quantum computing revolution. Molecular lanthanide cluster complexes comprising multiple Ln ions offer unrivalled control in the internuclear distances and donor-acceptor compositions, thereby allowing more sophisticated and efficient down converting devices to be prepared.
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 focuses on advancing the trustworthiness and usability of multi-robot systems, particularly in the context of swarm robotics.
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.
The aim of this project is to utilise state-of-the-art 3D lithography in combination with state of the art electrodeposition to realise magnetic nanowires with controllable “flying” domain wall qubits, paving the way towards a quantum computer based upon spin textures in 3D magnetic nanowires.
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 objective of this project is to develop an on-chip entangled photon source that can be integrated within a quantum cryptography system to enable ultimate security of digital communication based on the laws of quantum physics.
In the wake of growing data privacy concerns and the enactment of the GDPR, Federated Learning (FL) has emerged as a leading privacy-preserving technology in Machine Learning. Despite its advancements, FL systems are not immune to privacy breaches due to the inherent memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital.
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 PhD project will develop a new sensor technology to diagnose bacterial infections rapidly.
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.
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 aims to explore how Large Language Models (LLMs) can be harnessed to continuously acquire new skills to solve novel tasks as opposed to mastering a predefined and fixed set of tasks. In particular, methods for incrementally learning skill representations jointly from textual descriptions and spatio-temporal information of action sequences will be developed and evaluated on learning visuomotor robotic tasks in a household environment.
This PhD opportunity focuses on the development of Smart Acoustic Control Technologies, which bring together acoustic and structural design with advanced sensing, actuation, control, and signal processing technologies including machine learning. The developed smart systems offer significant potential to push the boundaries of noise and vibration control design and performance.
Advance the frontiers of active and polychromatic metasurfaces and metamaterials by exploring the theoretical, simulation, and experimental implications of space-time modulation.
This project will exploit computer simulations to investigate the dynamics of the generation of light in such large, few-mode or multimode, optical fibres.
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.
Developing a new generation of Thermoelectric generators for powering wearable devices from body heat
This project will investigated Reynolds scaling effects to help support the development of future aircraft.
The aim of this project is to leverage the potential of big data and AI to obtain a clearer insight into effects such as vehicle technical characteristics and driver/operator moods, preferences, and behaviours, and use these insights to improve existing operational and strategic policies. Relevant data from existing large vehicle fleets will be utilised to develop models that will be integrated into a prototype training platform to be used across different fleet operators in the UK and internationally.
Additive manufacturing enables the fabrication of engineering components with a high degree of geometric complexity. This geometric complexity makes the measurement and inspection of metal AM components very difficult. In this project, You will develop new methods for measuring and inspecting complex AM components.
This project will develop new methods for vortex flow prediction using advanced computational methods.
This project will initially focus on developing, demonstrating, and characterising fibre laser sources and will subsequently aim to utilise the developed technology in a range of application areas.
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 |
