Harnessing Bayesian statistics in the analysis of experimental problems

Diamond Light Source helps thousands of scientists each year collect experimental data. The analysis of this data is incredibly important, and in some circumstances, it can be very complex. Therefore, it is necessary to develop more advanced and intelligent ways of analysis.

X-ray reflectometry is an example of one of these experimental methods, which can be used to study the structure of biological cell membranes and photovoltaic materials. The analysis of X-ray reflectometry data relies on using sophisticated models that describe the material. We hope to improve the analysis of X-ray reflectometry data through the use of Bayesian statistics; which allows for the inclusion of prior information about the system. To achieve this it is necessary to construct a mathematical framework and implement this within an open-source analysis package.

This project will allow for the development of both mathematics and modern software engineering skills. The successful candidate will be exposed to the cutting edge of data science as applied to experimental physical and life sciences.