Environmental health plays a role in all of society and encompasses the core disciplines of public health, food safety and integrity, health and safety at work, environmental protection and housing and communities. The number of people who die every year as a result of living in unhealthy environments as a result of contaminated air, water and land, communicable disease, poor housing standards and dangers at work amongst other things is estimated to be 12.6 million people globally (WHO, 2016).
Environmental Health Practitioners (EHP) work in the public and private sector to keep people healthy, safe and reduce health inequalities (CIEH, 2023). They do this by acting as regulators; promoting compliance, good behaviour and practice, and enforce the law where required.
Recent global, national and local events including the coronavirus (COVID-19) pandemic, flooding, migration and the housing crises and others has put increasing pressure on frontline environmental health services to ensure compliance, implement enforcement and reduce health inequalities.
Most local authorities across the UK have reported being detrimentally underfunded over the past five years for key services like Environmental Health (Dickson et al., 2020). This has created a backlog of issues that need investigated and action taken, and has resulted in a shortfall of trained EHPs across the public sector (CIEH 2021).
Artificial intelligence (AI) has emerged as being an innovative technology which could transform how we live and work, including the delivery and efficiency of essential public services like environmental health (Schwalbe & Wahl, 2020). Using machine learning (MI) algorithms, it can analyse large volumes of complex data to find patterns and make predictions, often exceeding the accuracy and efficiency of people who are attempting the same task (NASEM, 2019). As such, the UK Government has recently pledged £118 million in funding to “put AI to work improving every element of Britons’ lives” (UK Gov, 2023).
There has been some limited application of AI technology to environmental health, most notably in air quality remote sensing, waste management and environmental epidemiology and pollution modelling (VoPham et al., 2018; Schmidt, 2020; Noh, 2021).
The application of AI to help improve environmental health service delivery and efficiency is largely unexplored, especially in terms of its accuracy in hazard and risk analysis, its usefulness in risk communication and in intervention decision-making (Anderson et al., 2023). With the current skills gap across the environmental health profession, the use and application of AI to relevant scenarios could help current EHPs regulate more effectively and efficiently and ultimately reduce health inequalities and the risk from other environmental health hazards (M. Bublitz et al., 2019).
This research seeks to explore the potential application, benefits and drawbacks to AI in addressing a variety of environmental health challenges and in reducing health inequalities.
Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.
We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.
In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.
Appointment will be made on merit.
The University offers the following levels of support:
The following scholarship options are available to applicants worldwide:
These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.
Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.
Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.
The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).
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. Further information on cost of living
Submission deadline
Monday 26 February 2024
04:00PM
Interview Date
Mid March 2024
Preferred student start date
16 September 2024
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