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PhD Studentship in Adaptive decision making under scarcity

University of Bath - Psychology

Qualification Type: PhD
Location: Bath
Funding for: UK Students, EU Students, International Students
Funding amount: £19,237 per annum
Hours: Full Time
Placed On: 24th September 2024
Closes: 15th December 2024

This project is being advertised as one that is in competition for a fully funded studentship. The successful candidate would work with the proposed supervisor to put forward an application to the ESRC South-West Doctoral Training Partnership.

In times of rising living costs, households living in poverty struggle to afford their basic needs. Tighter budgets imply that households experiencing poverty will more often have to make trade-offs and, for instance, decide whether to spend their budget on healthier food or warmer homes. So far, research has neglected how households experiencing poverty juggle their expenses to meet multiple goals. This PhD proposal bridges this gap by exploring how individuals living in poverty manage their financial budgets and balance conflicts between long-term goals and basic needs. The PhD project will seek to characterize the budgeting strategies of financially deprived and wealthier individuals through qualitative Expert-by-Experience approaches and cognitive modelling of decision strategies. Using reinforcement learning, the project further aims to determine how individuals adjust their budgeting strategies when economic market conditions or life circumstances change. The project will establish a critical evidence base for individuals, practitioners, and policy makers to draw upon when designing effective future interventions to fight poverty.

  • The successful candidate will join a multidisciplinary research team examining how financially deprived persons make household decisions under scarcity. Our supervisory team includes experts in decision science, economics, and social policy.
  • The ideal candidate will have a solid background in research methodology, a strong understanding of statistical modelling, and a keen interest in expanding their skills into reinforcement learning and computational modelling.

Please contact Janina Hoffmann for more information (j.a.hoffmann@bath.ac.uk)

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