Modelling impacts of simulated environmental social interventions for policy and community decision support

GALLANT’s (https://www.gla.ac.uk/gallant) virtual

data hub will bring to life the living lab of data collated and created through GALLANT on environment, ecology, place, people and communities. This will enable opportunities to learn about Glasgow’s ‘living space’, how it is changing, and what effect interventions may have on the future environment, economy, health and wellbeing for the city.

Key to future city planning for sustainable solutions is information from the integration of such data, engagement with communities and modelling of simulated scenarios/interventions, to develop tools to inform future decision making for policy and community action. 

This PhD will explore connecting data streams within the virtual data hub and developing visualisation/analytics/modelling tools to support future city planning.   It is of specific interest in this project to explore the effect of a range of interventions/simulated scenarios on community perception and participation in active travel (e.g. walking to school, cycling to work). There is a lack of knowledge on social cohesion metrics to inform what is needed to make a societal change in attitude. This project will specifically simulate and model interventions and scenarios to explore questions such as:

·      How do people perceive their community and their belonging to a community that might influence a change in their actions?

·      Is there a tipping point in community uptake that results in a larger change in participation in active travel in a community? 

·      How do we link and integrate these complex qualitative data types with other quantitative data streams and modelling to inform decision making?

The PhD student will work directly with a team of researchers at UoG, local communities, and colleagues at Glasgow City Council (GCC) to explore data connections, define specific scenarios of interest and develop visualisation and analytics approaches (including topics such as data linkage, agent based modelling, data fusion). The research will provide open-source tools aimed at decision support that integrate with the GALLANT virtual data hub, and support planning for future communities and policy.

The successful candidate for this post will demonstrate skills and experience in programming, analysing data, data analytics and modelling, and a strong interest in environmental and community based research. They will demonstrate the capability to work closely with a team of researchers and external stakeholders.

To be classed as a UK/Home applicant, candidates must meet the following criteria:

• Be a UK National (meeting residency requirements), or

• Have settled status, or

• Have pre-settled status (meeting residency requirements), or

• Have indefinite leave to remain or enter.

All applicants must have or expect to obtain a first-class degree (2.1 or equivalent) in an appropriate discipline. This may cover, but is not limited to, earth sciences, social science, mathematics, engineering, computing, physics, bio- and chemical sciences.

We champion Equality, Diversity and Inclusion, believing that this is the way to increase research productivity and quality and to enhance societal and economic impact. Likewise, the University of Glasgow and our external partners are fully committed to EDI principles.

We support applications from under-represented backgrounds, childcare support for conference attendance, flexible working for carers and promote a work-life balance.

For enquires related to EDI, please address to GALLANT EDI Champion, Dr Caroline Gauchotte-Lindsay via the GALLANT-phd mailbox.

How to Apply: Please refer to the following website for details on how to apply: https://www.gla.ac.uk/gallant. For studentship enquiries, please contact [Email Address Removed].