Project details
Are you passionate about robotics, AI, and revolutionizing healthcare? This PhD opportunity offers the chance to pioneer advanced robotic systems that will redefine rehabilitation for brain injury patients. Robotic systems have shown immense potential in assisting with recovery, but ensuring the safe and adaptive application of force in real time remains a critical challenge.
In this research, you will explore innovative solutions to improve patient outcomes through AI-enhanced robotic therapy. You will focus on developing adaptive soft robotic systems that deliver precise, real-time force control using deep learning and Finite Element Analysis (FEA). These breakthroughs will push the boundaries of robotics, contributing to safer and more effective rehabilitation therapies.
As a PhD candidate, you will:
- Lead the development of AI-driven soft robotic grippers for brain injury rehabilitation.
- Harness the power of deep learning to predict and control forces using FEA data.
- Gain invaluable experience in cutting-edge fields including robotics, machine learning, soft robotics, and predictive force control.
- Contribute to the growing field of medical robotics, directly impacting the lives of patients recovering from brain injuries.
This research has the potential to transform rehabilitation technology and revolutionize how therapy is delivered. Your work will address real-world challenges, bridging the gap between advanced robotics and healthcare.
We are looking for candidates who are highly motivated, with excellent programming skills and a strong passion for robotics and machine learning. Knowledge in soft robotics, deep learning, force estimation, and problem-solving will be an advantage.
Join us in shaping the future of rehabilitation technology. Apply now to make an impact in a rapidly growing and life-changing field.
The School of Mechanical, Electrical and Manufacturing Engineering has seen 100% of its research impact rated as ‘world-leading’ or ‘internationally excellent’ (REF, 2021).
Supervisors
Primary supervisor: Dr Behnaz Sohani
Entry requirements
Our entry requirements are listed using standard UK undergraduate degree classifications i.e. first-class honours, upper second-class honours and lower second-class honours. To learn the equivalent for your country, please choose it from the drop-down below.
Entry requirements for United Kingdom
2:1 honour degree (or equivalent)
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Fees and funding
Tuition fees for 2024-25 entry
UK fee
£4,786 Full-time degree per annum
International fee
£27,500 Full-time degree per annum
Fees for the 2024-25 academic year apply to projects starting in October 2024, January 2025, April 2025 and July 2025.
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.
How to apply
Applications should be made online. Under programme name, select ‘Mechanical and Manufacturing Engineering/Electronic, Electrical & Systems Engineering’ and quote the advert reference number UF-BS-2024 in your application.
To avoid delays in processing your application, please ensure that you submit your CV and the minimum supporting documents.
The following selection criteria will be used by academic schools to help them make a decision on your application.
