We offer a range of PhDs funded by different sources, such as research councils, industries or charities.
To apply for a funded PhD please read the advertised project information carefully as requirements will vary between funders. The project information will include details of funding eligibility, application deadline dates and links to application forms. Only applicants who have a relevant background and meet the funding criteria can be considered.
We invite applications for a fully funded PhD studentship at Lancaster University’s School of Engineering, in partnership with United Kingdom National Nuclear Laboratory (UKNNL). This exciting project will develop novel data-driven, robust, and adaptive control methods for human–robot interaction and teleoperation, with direct applications in nuclear robotics, hazardous environment manipulation, and beyond.
Teleoperation is a critical enabler for safe and efficient operation in hazardous environments such as nuclear decommissioning. However, current industrial solutions suffer from limitations under uncertainty, time delays, and noisy sensing.
This PhD project will design and experimentally validate a hybrid motion–force control framework that ensures precise end-effector positioning while maintaining robust and adaptive force regulation under real-world conditions. Research will include:
The project provides the opportunity to work on cutting-edge robotics challenges with significant industrial impact, supported by state-of-the-art facilities at both Lancaster University and UKNNL.
Applicants should submit:
Applications will be considered on a rolling basis until the position is filled, with an expected start date of January 2025.
Closing Date – 1st December
For informal enquiries, please contact Dr Allahyar Montazeri
Start Date: As soon as possible
Deadline for application: Open (it is recommended you apply as soon as possible)
Interview: Rolling
If you’re interested in protecting AI from rapidly emerging cyber threats and securing a technology that will define the coming decades, this PhD studentship is for you.
We are seeking candidates to join our AI security group at Lancaster University, and become part of this rapidly growing research field.
The adoption of Artificial Intelligence (AI) and prominent technologies such as Generative AI, LLMs, and Agentic AI systems is rapidly accelerating across both research and industry.
While there is considerable research activity on the application of AI for security, there has been less attention towards the security of AI itself. AI security focuses on addressing cyber security risks against the AI systems against a wide plethora of cyber attacks, spanning prompt injection, data leakage, jailbreaking, bypassing guardrails, model backdoors, and more. The emergence of such AI risks has drawn the attention of every nation and major business, however existing cyber security tools and methods are ineffective within AI systems due to the intrinsically random, complex, and opaque nature of neural networks. To date, how to secure today’s and tomorrow’s AI models and systems remains unsolved.
This project would provide you the skill and training necessary to become a researcher specializing in AI security – an area that is increasingly sought after in academia and industry.
Topics of interest you could pursue include:
We are among the few labs globally specializing in AI security. You will be part of a new cohort of PhD students joining an established team of scientists and engineers. Founded in 2016, the research lab led by Professor Peter Garraghan is internationally renowned in AI systems and security, publishing over 70 research papers, securing over £14M in external grant funding, the formation of Mindgard, and all research students to date securing positions in academia or industry R&D labs upon graduation.
These positions are available now, thus candidates are strongly recommended to apply as early as possible.
For informal enquiries about these positions, please contact and share your CV with Professor Peter Garraghan. To apply, please visit our school PhD opportunities page, which includes guidance on submission, and a link to the submission system.
Optimising recovery and return to combat readiness is key to ensuring military personnel are prepared for deployment in the UK and overseas. Utilising 3D motion capture for assessing gait of military personnel is the “gold standard,” but not logistically feasible due to the number of personnel requiring assessment, time taken to assess, digitise, and analyse the data, cost, and expertise to interpret it.
AI driven mobile phone applications that track gait have the potential to revolutionise how we assess gait and diagnose gait disorders not only in military personnel but all clinical populations. Their ease of use, speed of feedback and low cost makes them an ideal tool to be implemented into clinical practice, particularly in a rehabilitation setting.
We have developed a 3D human estimation pose model capable of capturing and measuring gait, but it has not been validated in a clinical population or been compared to the “gold standard” 3D motion capture. Our aim in collaboration with the Ministry of Defence is to adapt and refine our existing 3D human estimation pose model to be able to automatically detect and diagnose gait disorders in military personnel with overuse injuries.
We have four key objectives:
Objective 1: To adapt our existing model to capture and analyse biomechanical data from military personnel with and without overuse injuries
Objective 2: To determine the validity of the biomechanical data obtained from our model compared to the “gold standard” 3D motion capture in military personnel with and without overuse injuries
Objective 3: To identify, test, and validate possible solutions for the modelto diagnose gait disorders in military personnel with overuse injuries
Objective 4: Test real time execution of digitisation, application and data extraction when using the model to diagnose gait disorders in military personnel with overuse injuries
We are looking for an enthusiastic, proactive and highly motivated PhD candidate.
Experience in 3D motion capture, machine learning, AI or data analysis strongly desirable. This project is in collaboration with the Ministry of Defence, and some travel will be expected between Lancaster University (host institution) and the Defence Medical Rehabilitation Centre Stanford Hall for meetings, recruitment of personnel and data collection.
Essential:
Strongly desirable:
A successful applicant will receive a stipend towards living expenses at the UKRI rate (currently £ £20,780 per year) and £1000 per year to support training and development needs (e.g., attend courses or conferences).
Dr Hannah Jarvis - Lancaster University has expertise in gait assessment and led previous research projects with the Ministry of Defence. Co-supervisors are Professor Jun Liu - Lancaster University, expertise in computer vision and machine learning, and Professor Neil Reeves - Lancaster University, expertise in digital health technologies and cyber security. You will also be supervised by colleagues from DMRC Stanford Hall.
In your application, please include:
A cover letter detailing why you are the most appropriate person for the position
A CV
Application deadline 31st October 2025, 5pm
Interviews early November – date tbc
Please contact Dr Hannah Jarvis
You will need to put in an application to the University's online application system. Please follow the University's guidance regarding the required documentation.
Please make sure to include a CV (mandatory, maximum of two pages) including your previous degrees and graduation grades, as well as any relevant skills. Where it applies, also include awards of excellence, publications, and links to code releases, such as through GitHub.
Please follow all of the requirements. Not adhering to these requirements may at best delay the processing of your application, and at worst might result in immediate rejection. The preferred format for all supporting documents is PDF.
Please note that even if you are applying for a funded PhD position, you will need to develop a proposal.
At the top of the first page of the Research Proposal, please include the following information:
A personal statement is mandatory and should be a maximum of one page. The document should explain your motivation to work on your chosen project and a little about your background.
Studying for a research degree is a highly rewarding and challenging process. You'll work to become a leading expert in your topic area with regular contact and close individual supervision with your supervisor.
If you have your own research idea, we can help you to develop it. To begin this process you will need to find a PhD Supervisor from one of our research groups, whose research interests align with your own.
You can also apply for a PhD from one of the Doctoral Training Centres and Partnerships that work with the School of Computing and Communications. Details of each of the Training Centres are provided here.
