Funding

Competition funded (UK/EU and international students)

Project code

OSP50330125

Department

School of Organisations, Systems, and People

Start dates

October 2025

Application deadline

17 January 2025

Applications are invited for a fully-funded three-year PhD to commence in October 2025. 

The PhD will be based in the Faculty of Business and Law, and will be supervised by Dr Huijing Chen, Dr Adele Bezuidenhout and Dr Aamir Amin.

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 (£19,237 for 2024/25). Bursary recipients will also receive £2,000 for fieldwork purposes. 

Costs for student visa and immigration health surcharge are not covered by this bursary. For further guidance and advice visit our international and EU students ‘Visa FAQs’ page.    

The work on this project will explore:

 

  • How does an organisation select the most suitable forecasting methods for supply chain management
  • What types of data are useful for predictive analytics
  • How can AI help an organisation to understand and navigate complex contexts and build systems that are fit for purpose
  • How can human-AI complementarity be furthered when Machine Learning drives human learning in supply chains

In recent years thanks to the advances in technologies and availability of Big Data, Machine Learning (ML) and Artificial Intelligence (AI) have gained more popularity in forecasting. These methods provide a data-driven approach towards forecasting. Like the physical world, the development of AI techniques is experiencing a period of great turbulence and complexity, with lightning paces of traditional ML, the breakthrough of Deep Learning and eventually to generative AI all happening in the last 10 years or so.

As the world sees turbulence as the hallmark of the post-pandemic era and artificial intelligence (AI) development and adoption accelerates (Singla et al., 2024), Sanders (2024) recognised an opportunity, and an urgent need, for researchers in this “Inter-AI” period to shape an AI-enabled future, before norms, values and standards are embedded in AI systems and decisions automated.

In a Supply Chain Management context, this project aims to achieve human-AI complementarity by understanding how Machine Learning can drive human learning in organisations and supply chains. 

This project will use an organisational case study as the main methodology. Isle of Wight Tomatoes is the collaborator on this project, with the option of extending it to a 4-year industrial PhD. It has a unique position of being a grower (manufacturer), wholesaler to major supermarkets and a retailer (direct selling). The company is looking to integrate AI into its supply chain, but is struggling to unlock value in its business faced with many variables. This project’s focus on algorithms, data and contexts and their interplay aligns with the company’s strategy.

 

 

Entry Requirements

You'll need a good first degree from an internationally recognized university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an Information Systems/Information Technology/Social Sciences. 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.

Subject areas for first degree or Master’s should be in Management Science, Operational Research, Data Science/Analytics or related disciplines. Essential skills are Machine Learning, statistical modelling, predictive analytics and programming. Desirable skills: qualitative research methods and familiarity with Nvivo.


 

 

How to apply 

We’d encourage you to contact Dr Huijing Chen (huijing.chen@port.ac.uk) 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 OSP50330125 when applying. Please note that email applications are not accepted.