Vacancy overview: Fixed term contract for 36 months
The Behavioural Science Group in Warwick Business School are looking to appoint a full-time postdoctoral researcher for 36 months, in collaboration with the Gambling Commission, on a project examining gambling-related harms among the UK population. The project is led by Dr Naomi Muggleton, Prof. Neil Stewart (both of WBS), Ben Haden (Gambling Commission), and Prof. John Gathergood (University of Nottingham).
The project aims to protect vulnerable persons from being harmed or exploited by gambling using innovative data-centric approaches, and to produce internationally excellent new empirical research in behavioural and economic science. The research will leverage the Gambling Commission’s unique access to gambling operator data to address core theoretical questions about decision-making in behavioural and economic science and find answers with direct applicability to policymakers and industry.
The successful candidate will be based at Warwick Business School and join the prestigious international collaboration. They will develop high impact insights into gambling-related harm through application of innovative data science techniques. This will involve working with the Gambling Commission’s extremely lucrative access to play-by-play transaction data, providing rare insight into real-world decision-making in the domain of gambling and risk. They will then lead the writing and publication of the results.
Informal enquiries to Dr Naomi Muggleton ([email protected] ).
Job Description
As an applicant, you must:
- Have a PhD in psychology, economics, or other related discipline, or be about to submit your PhD.
- Be familiar with the psychology and economics of decision making and/or the study of gambling-related harms.
- Have expertise in using R and/or Python to work with large data sets.
- Have experience writing up research for publication in scientific journals.
Having experience of the following would an advantage:
- Data base query languages like SQL and experience with econometrics and machine learning.
- Analysis of moderate to large data sets.
- Presenting to academic and industry audiences
- Building productive relationships with the empathy to understand other people’s perspectives and the ability to simplify, articulate, and explain complex ideas to non-specialists.
Closing date
8 January 2023
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