Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Uchenna Ogenyi.


The work on this project will:

  • Investigate and analyze the dynamics of human-robot teams in healthcare settings. Understand the roles, responsibilities, and interactions between human caregivers and robotic assistants.
  • Develop algorithms and systems that facilitate collaborative task planning between humans and robots. This involves optimising task allocation based on the strengths and capabilities of each team member.
  • Implement adaptive learning mechanisms that enable the robot to learn and adapt its behaviour in response to human preferences, work patterns, and changing healthcare requirements.
  • Validate the effectiveness of the optimised human-robot teaming through simulations and, when feasible, real-world trials in healthcare environments. Gather feedback from healthcare professionals for continuous improvement.


There is a current deficit of skilled personnel in the healthcare sector, a challenge exacerbated by the growing demand for healthcare professionals due to the increasing elderly population. This poses a multifaceted sociopolitical and economic challenge. The anticipation is that there will be a significant increase in human-robot collaboration within healthcare in the near future. This is foreseen as a valuable advantage, offering relief to healthcare professionals through the integration of technical systems.

By optimising the collaboration between humans and robots in healthcare assistance, this project aims to contribute to the development of advanced methods that enhance the overall quality of healthcare delivery, improve efficiency, and provide a positive experience for both caregivers and patients. The optimised collaboration is anticipated to revolutionize healthcare assistance, setting new standards for the integration of human and robotic efforts.

This initiative encompasses a multifaceted approach with a focus on several key areas:

The project delves into the analysis of team dynamics within human-robot collaborations in healthcare settings. Understanding the roles, responsibilities, and interactions between human caregivers and robotic assistants forms a crucial foundation. A significant aspect involves developing algorithms for collaborative task planning. This includes optimizing task allocation based on the unique strengths and capabilities of each team member, fostering a more efficient workflow. To adapt to dynamic healthcare scenarios, the project implements adaptive learning mechanisms for the robot. This allows it to learn and adjust its behaviour in response to human preferences, work patterns, and evolving healthcare requirements.



Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Applicants should possess a solid understanding of the core principles in robotics, computer vision, and machine learning techniques. Proficiency in Python/C++ programming, strong analytical skills, and a foundation in computer science or related field are essential requirements. The ideal candidate must demonstrate the ability to think critically and independently, including the formulation of research problems. Additionally, effective oral and written communication skills, along with proficient time management, are highly valued.


How to apply

We’d encourage you to contact Dr Uchenna Ogenyi ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: COMP6241025