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Exploring health and health inequality impact of urban green and blue spaces using Data Science Techniques

Project Description



66% of the world now live in urban settings. Urbanisation is forecasted to keep growing putting ever increasing stress on resources and human well-being. According to the world health organisation urbanisation increases health inequalities and prevalence of non-communicable diseases. For example, mental health issues in urban settings is forecasted by WHO to be the leading cause of death by 2030. In most disadvantaged urban areas exposure to non-communicable disease and poor mental health predominantly clusters. This is compounded by climate change.

It is thought that urban green and blue infrastructure, that is urban water ways such as river and canals and their green banks, could have a salutogenic effect on urban population. This could be potent as it is forecasted that 50% of the global population will lives within 2 kilometres of urban inland waterways. Urban water ways manage crucial water resources but are also linear recreation parks, traffic free commuting routes, flood and heat mitigation systems, tourist attractions and social places. Green and blue spaces are under-utilised assets which interact with health, economic, education, transport and housing systems, The issue is that there is a limited evidence base about how to leverage this potential to prevent non-communicable diseases (cardiovascular diseases, respiratory diseases, diabetes and mental health) and ensure health equity and resilience.


This PhD will focus on building data centric models of health and health inequality effect of urban green and blue spaces. This will require the application of Machine Learning and Bayesian based techniques to spatial-temporal health data. The project may explore the relationship different type of urban green and blue infrastructure and health and health inequality; quantify the temporal and geographical spread of these effects, quantify the cost benefit of green and blue infrastructure; quantify the impact on inclusiveness and age friendliness of cities.


The successful applicant will be a Computer Science, Artificial Intelligence, Mathematics or a Applied Health degree (with a statistical component) graduate holding the minimum of a first degree (2:1 or above); or a Masters degree in a subject relevant to the research project. The successful candidate should demonstrate the capability to work across a diversity of technical areas with an inquisitive and problem solving approach and have excellent knowledge and experience of programming and analytical skills.

Research Strategy and Research Profile

Glasgow Caledonian University’s research is framed around the United Nations Sustainable Development Goals (, We address the Goals via three societal challenge areas of Inclusive Societies, Healthy Lives and Sustainable Environments. For more ( This project is part of the research activity of the Research Group – Artificial Intelligence

Fixed part of the Project Description – If there is something here that you wish to modify, please highlight this to your research degree administrator.

How to Apply

Applicants will normally hold a UK honours degree 2:1 (or equivalent); or a Masters degree in a subject relevant to the research project. Equivalent professional qualifications and any appropriate research experience may be considered. A minimum English language level of IELTS score of 6.5 (or equivalent) with no element below 6.0 is required. Some research disciplines may require higher levels.

Candidates are encouraged to contact the research supervisors for the project before applying. Applicants should complete the online GCU Research Application Form, stating the Project Title and Reference Number (listed above).

Please also attach to the online application, copies of academic qualifications (including IELTS if required), 2 references and any other relevant documentation.

Please send any enquiries regarding your application to: Applicants shortlisted for the PhD project will be contacted for an interview.

For more information on How to apply and the online application form please go to

Professor Gordon Morison

Funding Notes

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