Summary

This study will focus on driving efficiencies across the food supply chain by creating a predictive tool to reduce food waste among retailers. Combining big data relating to inventory, sales and food waste alongside other uncontrollable factors (e.g. weather conditions, transport strikes, changing consumer behavior, etc.), a predictive tool will be developed to support managerial decision-making on how to effectively redistribute and reuse food, that may otherwise be wasted.  Focusing on fresh food waste, specifically, fruit and vegetables, this project has the following key objectives/stages:

1.Context setting – Review of current UK government/policies on Food Waste.

2. Systematic Literature Review – Identification of controllable and uncontrollable factors impacting on food waste prediction within retailing.

3.Qualitative – mapping the fresh food supply chain across one food retailer.

4.Quantitative - Development of database – integration of big data across each stage of the supply chain and additional data on external factors (e.g. weather, transport strikes, changing consumer behavior, etc).

5.Quantitative - Development of AI algorithms - predictive analytics will be used to develop algorithms which will accurately forecast the potential for food waste within the fresh fruit and vegetable category.

6.Testing predictive tool – the tool will be tested in a retail setting. Perceptions of the usefulness of this tool for informing managerial decisions will be explored and used to inform the final stage of the study.

7.Recommendations – a set of managerial and technical recommendations will be made to improve the future viability of applying the algorithm to other categories within the food retail supply chain.

Advanced AI algorithms will be developed on data supplied by our industrial partner Sonae Retailing, a leader in this area who has published a White Paper "The Future of Food” which outlines key recommendations on how EU and national policymakers can help foster innovation and cooperation in the food sector.

This successful candidate for this PhD project will work within Intelligent Systems Research Centre (ISRC) and focus on innovations in intelligent systems and data analytics to develop novel analytical methods in one or more the following areas  :

*Self-organising fuzzy neural networks

*Mixtures of neural experts

*Hidden Markov Models

*Monte Carlo Methods

*Bayesian Networks

*Reinforcement learning

*Predictive modelling

The project will therefore involve contributions to fundamental methods and validation of these methods on challenging real-world datasets. The PhD candidate will have access to state-of-the-art hardware and software for data analytics, a high performance computing facility, as well as computational modelling techniques and will be integrated within and learn from the Cognitive Analytics Research Laboratory (CARL) team of data scientists and engineers with specialist knowledge in various domains as well as from multi-disciplinary teams of researchers at the ISRC. There is significant demand for expertise in data analytics. The PhD opportunity will enable the successful candidate to gain that expertise and to push the boundaries on the state-of-the-art, and apply their knowledge to develop solutions to challenging industry led problems that will have a significant global impact.


Essential criteria

  • To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
  • Experience using research methods or other approaches relevant to the subject domain

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 70%
  • For VCRS Awards, Masters at 75%
  • Publications - peer-reviewed

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 15,500 (tbc) per annum for three years (subject to satisfactory academic performance). EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies



The Doctoral College at Ulster University


Reviews

Profile picture of Adrian Johnston

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

Watch Video  

Profile picture of Huan Wan

I started my PhD at Ulster University after I received the master degree in computer application and technology from the School of Mathematics and Computer Science, Fujian Normal University, China. My research interests are feature extraction, face verification and pattern recognition.The proudest moments of my PhD when my papers were accepted by journals and I received my PhD certificate. It is a long journey to pursue a PhD, I couldn't have got through this without the constant support, help and encouragement from my supervisors and friends. Many thanks all of them.

Huan Wan - PhD in Computer Science and Informatics


Profile picture of Xin Wei

I received the bachelor’s of engineering degree in computer science and technology from Shangrao Normal University, Jiangxi, China, in 2013; and the master’s degree in computer application and technology from the School of Mathematics and Computer Science, Fujian Normal University, China. When I was pursuing a PhD degree at Ulster University, I continued my research on face recognition and image representation.This long journey has only been possible due to the constant support and encouragement of my first supervisor. I also like to thank my second supervisor for his patience, support and guidance during my research studies. My favourite memory was the days of exercising, gathering and playing with my friends here. If I could speak to myself at the start of my PhD, the best piece of advice I would give myself would be "submit more papers to Journals instead of conferences".

Xin Wei - PhD in Computer Science and Informatics


Profile picture of Niloofer Shanavas

After master’s degree, I joined the Artificial Intelligence Research Group in the School of Computing at Ulster University to pursue my PhD. I would like to thank my supervisors for their guidance, invaluable advice, encouragement and support throughout my PhD.My proudest moments were when my research papers were accepted in prestigious conferences and journals. I feel accomplished about the six first-author publications from my doctoral research. Also, I have had the honour of receiving the Best Student Paper Award at the 2018 International FLINS Conference.I love travelling; my favourite memories were travelling to present my research in addition to getting the opportunity to meet leading researchers from different parts of the world. And I couldn't have achieved this without the support of my friends and family.

Niloofer Shanavas - PhD in Computer Sciences and Informatics


Profile picture of Jyotsna Talreja Wassan

In the whole PhD ordeal, my supervisory team played a tremendous role:- they are three in a million. They are perfect supervisors who perfectly know which milestones or pathways to be taken during research initiatives, and they understand the roles of virtually all stages in the journey of PhD. They showcased superior abilities in managing and motivating me evoking high standards; demonstrating a commitment to excellence. Jane and Haiying guided me as their daughter and Fiona turned out to be the best of friends.I heard from “Eleanor Roosevelt” that “The future belongs to those who believe in the beauty of their dreams.” The dream with which I grew up to become a Doctor one day, has finally come true. In the journey of PhD, I embraced that a PhD is not just the highest degree in Education but rather it is a life experience where perseverance is the key. I can never forget words from my external examiner Prof Yike Guo, from Imperial College London. His words

Jyotsna Talreja Wassan - PhD in Computer Science and Informatics