PhD Project opportunities

Welcome to our "project matching" service for the current Industrial Doctorates call for funding. The following list shows a range of potential PhD / EngD projects suggested by academics from Scottish universities.


The following project opportunities are open for Scottish businesses or public sector organisations interested in collaborating with Scottish Universities and benefit from an applied research project with a doctoral student. Funding is available through our current call for funding. If any of the following projects are of interest to you or your organisation, please get in touch.

If you are a prospective doctoral (PhD / EngD) student interested in applying for one of our current vacancies, please visit our industrial doctorates page.



Machine Learning For Security of Underwater Wireless Sensor Networks

My research core theme is based on Machine Learning for security of Underwater Wireless Sensor Networks for Intrusion Detection. The applied business domain is for underwater surveillance and monitoring products. The innovation in the project is derived from using the machine learning framework with multi-objective optimization. The intrusion detection application is based on data analysis of underwater noise database. The technical outcome of the project is a sonar based real time surveillance system. This project can be useful for surveillance and monitoring of Scotland’s tidal energy farm and Microsoft data center underwater.

Contact the Academic Supervisor, Dr Mohammad Hamdan, M.Hamdan@hw.ac.uk, for further information

Realising a Flexible Quality Framework for Managing Data Assets

This project will explore the following questions:

- How can data veracity measures (metrics) be encoded and enacted within a data ecosystem?

- How can data provenance be used to support new forms of veracity checking and anomaly detection?

- How can data policies be framed to reason about data veracity, and recommend appropriate decision-making actions?

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Transparent & Accountable Data Management for the Internet of Things

Building on an existing portfolio of research into data transparency and provenance, the proposed project will examine the following questions: What characteristics of IoT devices and their behaviours are necessary to formulate a model of transparency? How do we represent norms against which devices (and the ecosystems of which they are a part) can be held to account?

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Big-data and AI-based personalised flood preparation and evacuation system

This project is targeted to couple a coastal flood model and a transportation network with the big-data flood monitoring platform that we developed in Wang et al. (2018). The coupling will allow us to use the flood model to predict the flood development and the transportation model to optimise the flood evacuation routes.

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Using data science to understand the food system

In this project I would propose to look at available data on some aspect of the food system and see if we can use that to inform modelling and make predictions about how to improve or optimise the system. The area could be at the food production end of industry or the retail end. It depends on who has got data that they think they could make more of, in terms of using it to make forecasts about yield, or sales, for example.

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