Login | Sign up

PhD studentships in complexity economics at Oxford

The Complexity Economics Group at the Institute for New Economic Thinking at the Oxford Martin School has funding for several PhD students to work on a new project directed by Doyne Farmer to model the economy from the bottom up. The students will be part of a vibrant group of around 20 students and postdocs working on all aspects of economics using complex systems methods. The project will be based on fine-grained data sets with the goal of providing a detailed understanding of the rich and heterogeneous behavior underlying business cycles, inflation, interest rates, technological innovation and long term development.

The ideal candidate should have a background in quantitative sciences (economics, mathematics, statistics, physics, computer science, etc.), and a strong interest in economics and complex systems. Key skills include programming and data analysis, presentation skills, working in an interdisciplinary team, and an interest in macroeconomics, technological change, finance, network science, and economic history.

Candidates will need to apply for a DPhil (Oxford’s PhD) in either the Mathematical Institute or the Department of Geography. The deadline is January 25, 2019; it is also possible to apply until March 1, but the admission rate is lower. Upon being accepted, the project will pay stipend, tuition and college fees. Prospective candidates should contact Doyne Farmer (doyne.farmer at inet.ox.ac.uk) and François Lafond (francois.lafond at inet.ox.ac.uk) as soon as possible with a CV and a brief letter of motivation.

CountryUK
LabOxford, INET
Deadline25/01/2019 23:59
KeywordsComplexity Economics;

Recover your password

Please, provide the email you used to register. We will send an email to that address with a link that will take you to the reset password page. After resetting your password you will be automatically logged in to the system.

Already a member?

If you had an account on the old website, please provide the email you used to register there. After resetting your password you will be automatically signed in to the system.

Already have an account? Log in