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PhD position on ABM in popuulation health

At the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, we are looking to develop the next generation of highly skilled researchers. Our Unit has a particular focus on developing and using cutting-edge methods to understand how social, behavioural, economic, political and environmental factors influence health.

PhD topic: Agent based models in population health. Many population health issues are driven by interacting behavioural, environmental and social factors. Agent-Based Models (ABMs) allow us to examine how multiple, complex patterns of interactions between individuals, their health behaviours and their surrounding environment, combine to determine population patterns in health outcomes. We are interested in supervising PhD students to either (i) develop ABMs to assess the health outcomes of welfare reforms (such as the Universal Basic Income), or to investigate the provision of social care; or (ii) develop procedures and software tools for the application of machine learning and deep neural networks to the analysis of ABMs.

Lead supervisor: Dr Eric Silverman,

PhD topic: Development of a pervasive multi-sensor device to measure the ‘active ingredients’ of the relationship between nature and child health in Early Learning and Childcare settings. The natural environment affects our physical and psychological health. A number of hypothesised pathways exist, including physical activity, air quality, psychological restoration, and improved immune functioning. The Scottish Government are investing £2 billion into the expansion of Early Learning and Childcare (ELC), with a considerable amount of this money being earmarked to develop outdoor, nature-based nursery provision. This provides us with a unique opportunity to measure natural and artificial environmental attributes (e.g. light, temperature, negative air ions, organic compounds, air pollution) that may impact on the health and wellbeing of young children. The studentship will develop a robust, valid and reliable multi-sensor system that can be deployed in an ELC setting allowing us to measure, store, and transfer collected data.

Due to the project’s focus on sensor technology, electronics, and software integration, this studentship would suit a candidate with a background in computer science or electronic engineering. If the candidate has worked in industry this may be of value but there is an expectation that the candidate may be recently qualified at Masters level. Any experience in fields related to public health (e.g. Health Psychology, Epidemiology, Systems Science, Programme development) would be advantageous, as would any experience with environmental sciences as it may apply to human health.

For further information, please contact the supervisor team Dr Paul McCrorie (, Dr Anne Martin ( or Dr Kevin Worrall (

The deadline for applications is 24th February 2020 with a start in September 2020. Find out how to apply here:

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