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Fully-Funded PhD Studentship: Learning in Uncertain and Social Environments.

Applications are invited for a fully funded 3-year PhD studentship under the supervision of Dr. Paul Rauwolf in the School of Psychology at Bangor University, commencing between August 2021 and January 2022. The position can be held as full or part-time. The studentship covers the full cost of tuition fees, plus a tax-free maintenance stipend of approximately £15,200 per annum for three years and a research allowance of £750 per annum.

This project will focus on understanding and improving how individuals make decisions and solve problems in uncertain, social environments. Individuals must often simultaneously learn about an uncertain world while learning about and adapting to the behaviours of others who affect that world. An example of this are collective action problems, where groups of individuals are tasked with managing a valuable but vulnerable resource over time. History demonstrates that humans are not great at sharing and managing resources during uncertain times; for instance, during the Covid-19 pandemic many communities depleted their food and health-care resources. The underlying causes of poor sustainable behaviour, however, are less well-known. In particular, we do not know much about how individual characteristics (such as impulsivity or vulnerability to health problems) interact with how individuals navigate and learn from others. It is difficult to disentangle the individual and social factors leading to poor sustainable behaviour when environmental and social behaviours are constantly changing as a reaction to each other. Learning more could help us improve policy interventions to help people make better decisions about shared resources.

We will use advances in machine learning and Artificial Intelligence (note: no knowledge of machine learning is required for this post) and place individuals and computer partners in a social dilemma, where the group is tasked with maintaining a shared resource. We will manipulate the strategies and learning algorithms of the computer partners in the social dilemma to find which kinds of social norms best enable individuals to socially learn about maintaining a resource over time. We will also consider whether the best social environment for learning differs by individual characteristics such as impulsivity and vulnerability to health problems.

For full information, including how to apply, please go to:

If you have questions, please contact Dr. Rauwolf: