Applicants are expected to have an interest in wellbeing and its intersections with biology and social justice. The different studentships put different emphases on these three elements, but all the studentships explore the intersections, using different methods, with these three areas. We expect students to be experienced in appropriate methodologies, both quantitative and qualitative, as well as to have qualifications relevant to each PhD.
An excellent undergraduate degree with Honours in a relevant business, scientific/technological or social science subject
A Masters degree (or equivalent).
Students may also have other relevant experience or skills which are relevant to this project.
Candidates who are not native English speakers will be required to provide evidence for their English skills (such as by IELTS or similar tests that are approved by UKVI, or a degree completed in an English speaking country). The scholarship covers Home/EU/RUK fee rate only.
This proposal connects four, three year PhDs in inter-related projects examining improvement science, data science, disadvantage and social justice. It presents a series of projects designed to overlap and inform one another to create a cohort of researchers generating work with the potential with significant impact.
PhD one – improvement science and families in chaotic circumstances in Scotland
This PhD aims to construct a robust understanding of complex interventions and apply them to the case study of families in chaotic circumstances Scotland. The PhD aims to answer the following questions:
- How can we develop an academically-robust model of complex interventions that take account of behavioural research?
- How can complex interventions inform, and help develop, interventions in the lives of families in chaotic contexts?
- What can we learn through the application of complex models to the case of families in chaotic contexts in Scotland?
PhD two – data science and health outcomes
This PhD aims to develop data science approaches, especially based around machine learning, and apply them to develop strong understandings of large datasets which are already held by Scottish government and by the Beatson institute. It will aim to develop predictive models of health outcomes based on social drivers, especially those of families in chaotic contexts. This will allow social and clinical outcomes to be assessed on a systems-wide basis and cancer risk especially modelled through incidence of childhood trauma.
- What can data science methods add to more traditional approaches to health modelling?
- What can data science methods add to our understandings of the role of childhood trauma in subsequent health outcomes, especially in relation to cancer risk?
- How can we use data science to generate a scoring system for families in need of help where we might intervene early to prevent adverse social outcomes later in their lives?
This project is about predictive modelling but also machine learning. It would examine data for 700 families identified by health visitors in Renfrewshire in relation to adverse childhood experiences and examine the extent to which new measures or systems might supplement those already in place.
PhD three – the biological bases of disadvantage
This PhD aims to make the links outlined in existing research that span from neuroscientific understandings of child development, through to societal disadvantage in adults. These links have previously been given in brief terms in social research from Wilkinson, and Marmot, but there now exists the opportunity to provide a ‘joined-up’ account of social disadvantage, which can help underpin a clearer of how we might address social disadvantage – a science of wellbeing.
- How can we ‘join-up’ different understandings of the causes of social disadvantage from the micro to the macro level?
- What would this ‘joined-up’ understanding of social disadvantage mean for our understanding of how we might improve wellbeing?
- How does this new understanding of social disadvantage and wellbeing compare to existing understandings of wellbeing improvement? What might this new understanding contribute to debates about how we measure national wellbeing rather than Gross Domestic Product?
- To what extent can childhood disadvantage be overcome in later life? Which interventions have the best chance of working, and when should they be introduced?
PhD four – social justice, biology and behaviour
This PhD aims to examine how current theories of social justice can be enhanced through a more biologically-informed understanding of the effects, especially, of childhood trauma. It examines the linkages between social justice (a key area for the Scottish government), theories of social justice, biology and behaviour to form a nuanced understanding than is often current shown in any of these fields separately.
- What assumptions about biology and behaviour do current theories of social justice hold?
- Are these assumptions sustainable in the light of new insights from biology (especially in relation to childhood trauma) and behavioural science (especially Kahneman and Sunstein)?
- How can existing theories of social justice be adapted to shape policymaking in respect of achieving greater social justice? What would need to changing in policymaking?
- What specific interventions might be best supported by new theories of social justice that are more rigorously underpinned by biological and behavioural research?
How to apply
Please submit a CV, and a separate statement of not more than 1000 words explaining the relevance of your experience and qualifications to one or more of the projects above, making clear which project or projects you would like to be considered for.
Submit the two attachments to an email addressed to firstname.lastname@example.org by 12pm on 1st November 2017.