PhD Studentship in Neuroeconomic Decision Theory

Updated: 14 days ago
Location: Lancaster, ENGLAND
Job Type: FullTime
Deadline: 30 Jun 2024

Lancaster University Management School Department of Economics invites applications for a funded PhD studentship within the nascent field of Neuroeconomics.

The post-holder will engage in four-year, full-time, Economics PhD training from October 1st , 2024, under the primary supervision of Professor Carlos Alós-Ferrer.

The studentship cover tuition fees for four years and includes a generous living allowance.

The successful candidate will need to have a familiarity with either data analysis orformal-analytical modeling. Programming skills are a plus. Applicants should normally have, or be on track to obtain, an MSc degree in Economics, Psychology, Mathematics, or a related field, but candidates with other quantitative backgrounds could be considered.

The PhD project will require the post-holder to work across disciplines (economics, psychology, decision neuroscience, or mathematics, depending on the post-holder’s background and qualifications). The project is concerned with why and how humans make mistakes in their economic decisions, from the psychological and neural roots of persistent errors to the economic consequences of cognitive failures. It requires a willingness to work with process data, including response times and, potentially, eye-tracking and neural data.

The project specifics will be tailored to the post-holder’s skills and interests and can be more experimental/applied or analytical/mathematical.

Lancaster University’s Economics PhD programme is aimed at high-calibre students who wish to pursue a research career. The Department has a strong group in Behavioural and Experimental Economics and hosts a modern experimental lab (LexEL).

It is part of the Lancaster University Management School (LUMS), a triple-accredited and world-ranked management school with a reputation for outstanding research.

In the UK’s latest Research Excellence Framework, REF 2021, 90% of LUMS research was rated world leading or internationally excellent. The School was rated first for Research Power among all UK business schools – recognising the breadth and depth of our work – and equal-first for our Research Environment, recognising our proficiency in developing the next generation of researchers.

The successful applicant will acquire knowledge and skills in economics and psychology, through initial coursework and continuing training, and co-authoring research papers. The post-holder will have access to advanced research training courses at LUMS and nearby institutions. They will be expected to participate in research activities such as the department’s internal/external/PhD seminar series, and interdisciplinary workshops and conferences, both national and international.

How to apply?

Informal enquiries can be addressed to [email protected]

Applications should be made only through the Economics Department PhD application portal:

www.lancaster.ac.uk/study/postgraduate/postgraduate-courses/economics-phd

To apply, please provide a Personal Statement outlining your background, suitability, motivation, and any previous experience relevant to the project. Please mention that you are applying for the PhD position in Neuroeconomic Decision Theory. In addition, please submit a Research Statement which outlines your research interests – including any ideas you have that relate to the project. If you have participated in any research projects, please explain your role in those.

In the application portal, please submit this Research Statement in lieu of a Research Proposal.

Applicants must also submit: a CV, Academic transcripts (bachelors and masters), two academic references (names and contact data—no letters), and evidence of English language proficiency (if necessary). Applicants might also submit a sample of research work, e.g. a Master Thesis (or draft thereof).

Applications will be reviewed as they arrive and the post will be filled as soon as possible (but no earlier than June 30th 2024).