Funded (UK/EU and international students)

Project code



School of Strategy, Marketing, and Innovation

Start dates

October 2023

Application deadline

6 April 2023

Applications are invited for a fully-funded three year PhD to commence in October 2023. 

The PhD will be based in the Faculty of Business and Law, and will be supervised by Dr Emre Cinar, Professor Chris Simms and Dr Zeeshan Bhatti

Candidates applying for this project may be eligible to compete for one of a small number of bursaries available. Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the UKRI rate (£17,668 for 2022/23). Bursary recipients will also receive a contribution of £2,000 towards fieldwork. In addition, the Faculty supports conference costs with a contribution of £550 and training costs with a contribution of £450.

The work on this project could involve:

  • Exploring global best practices of AI adoption in the health sector and the current adoption projects in the NHS 
  • Providing in-depth understanding of the multidisciplinary challenges of collaborative innovation, big data and the government context and their influence in the deployment of AI innovations         
  • Developing coping strategies for the successful adoption of AI innovations in NHS 
  • Providing recommendations to the government and practitioners on the deployment of the AI based innovations


Innovation in the public healthcare sector is of critical and growing importance, specifically in the context of the UK`s ageing population and the long-term effects of the Covid-19 pandemic (Woolliscroft, 2020; Brem et al., 2021). AI forms a critical part of the next wave of innovations to revolutionise healthcare services. For example, AI offers the potential to effectively recognise abnormalities such as cancers on scans or to recommend treatments options, and could thus significantly improve effective early diagnosis, help address long waiting lists and improve patient outcomes. Without new technologies, the healthcare sector will struggle to continue to provide services that meet the needs of society and there is a critical need for change. The NHS has a long history of reform and innovation (see Farchi & Salge, 2017; Ferlie, 2017). Innovations based on big data and artificial intelligence (AI) are one of the top items on the current NHS improvement agenda and the UK Innovation Strategy (Department for Business, Energy & Industrial Strategy, 2021). However, there have been criticisms that the NHS historically faced significant problems while adopting digital innovations (Asthana et al., 2019).

Research on AI based innovations in the public sector healthcare is at its early stages. Prior studies have focused on the development of AI solutions and AI systems design. The management of their development and subsequent adoption have largely been overlooked. Preliminary research on AI based health innovation adoption has identified that alongside the technical difficulties of big data and AI development, a variety of actors and their interactions (due to the collaboration and contextual influences) lead to additional social, economic, political and legal, and organisational challenges (Sun & Medaglia, 2019). This creates a need to understand the challenges and coping strategies, beyond algorithm and system development activities, in the actual adoption and implementation processes to create managerial and policy related lessons.

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

You'll need an understanding of innovation management. We also encourage applicants from different backgrounds, who are knowledgeable about public sector as the context. Qualitative research skills and the willingness to develop them further during the PhD project is desirable.  



How to apply

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

When you are ready to apply, you can use our online application form. 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.

Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.

If you want to be considered for this funded PhD opportunity you must quote project code SM&I8180423 when applying and submit all required documentation.