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Big computations and big data = robust results?

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Analyses involving large quantities of data or complicated computer models are the norm nowadays across most of science. These analyses can be computationally expensive and require many assumptions to make them feasible in a reasonable amount of time. As such, analyses are rarely repeated and little is done to check the robustness of the results to deviations from the underpinning assumptions.

The proposed project follows on from "A Bayesian computer model analysis of Robust Bayesian analyses" by Vernon and Gosling. Here we utilised emulation technology to allow practitioners to check the robustness of their analyses and to highlight aspects of the analysis that are sensitive to changes in the assumptions.

This project will extend this work and demonstrate the method’s utility for several real examples from climate science to toxicology.

Funding Notes

This project is open to self-funded students and is eligible for funding from the School of Mathematics Scholarships, EPSRC Doctoral Training Partnerships, and Leeds Doctoral Scholarships.

All successful UK/EU and international applicants will be considered for funding, in an open competition across the School of Mathematics. To be considered for this funding, it is recommended to apply no later than 31 March 2018 for funding to start in October 2018. However, earlier applications are welcome, and will be considered on an ongoing basis.

Related Subjects

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