Uncovering the relationship between commuting, mental health and income in the UK and its geographical underpinnings
- Supervisors: Dr Carmen Cabrera-Arnau Dr Francisco Rowe Dr Mark Green
The increasing availability of transport gives us an unprecedented degree of flexibility regarding the locations where we live and work. This is evidenced by the more than 24 million people who commute to work in England and Wales, which represents around 90% of the workforce. While our society recognises the importance of well-being in the workplace, there is a complex relationship between commuting and mental health which remains to be fully understood.
The aim of this project is to conduct a comprehensive study on the interplay between commuting, mental health and income in the UK. A special emphasis will be placed on understanding the geographical underpinnings of this relationship. The objectives are:
(1) Examine the geography of commuting behaviours and mental health in the UK, as well as their relationship.
(2) Assess the extent to which the relationship between commuting and mental health is conditioned by the income level of commuters.
(3) Building upon (1) and (2), study the interplay between commuting, mental health and income in the UK, and the role of geography in shaping this interplay.
The study design involves analysing large-scale datasets and using methods for statistical and spatial modelling such as generalised linear regression, structural equation modelling and multiscale geographically weighted regression.
The project will be based in the Geographic Data Science Lab (GDSL), a highly interdisciplinary research group within the Department of Geography and Planning. The successful candidate will be given opportunities to undertake training, attend conferences, and interact with researchers in other universities.
Whilst this PhD will take place in the Department of Geography and Planning, the project sits more in the field of data science and statistical modelling. As such, it is essential to have experience with data science and/or statistics. The ideal candidate would have a background in a subject with a highly quantitative component such as mathematics, statistics, physics, computer science, economics or quantitative geography.
Start Date: 1st October 2023
This PhD project is funded by The Faculty of Science & Engineering at The University of Liverpool and will start on 1st October 2023.
Successful candidates who meet the University of Liverpool eligibility criteria will be awarded a Faculty of Science & Engineering studentship for 3.5 years, covering UK tuition fees and an annual tax-free stipend (e.g. £17,688 p.a. for 2022-23).
Faculty of Science & Engineering students benefit from bespoke graduate training and £5,000 for training, travel and conferences.
The Faculty of Science & Engineering is committed to equality, diversity, widening participation and inclusion. Academic qualifications are considered alongside non-academic experience. Our recruitment process considers potential with the same weighting as past experience. Students must complete a personal statement profoma and ensure this is included in their online application.
How to Apply:
All applicants must complete the personal statement proforma. This is instead of a normal personal/supporting statement/cover letter. The proforma is designed to standardise this part of the application to minimise the difference between those who are given support and those who are not. The proforma can be found here: https://tinyurl.com/ym2ycne4. More information on the application process can be found here: https://tinyurl.com/mwn5952t. When applying online, students should ensure they include the department name in the ‘Programme Applied For’ section of the online form, as well as the Faculty of Science & Engineering as the ‘studentship type’ in the finance section.
Application Web Address: https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/
Open to UK applicants
UK students are only eligible for a fully-funded Faculty of Science & Engineering studentship; overseas students are eligible to apply if they can financially cover the difference in UK and Overseas tuition fees, cover the costs of their student visa, NHS health surcharge, travel insurance and transport to the UK, as these are excluded from the funding.