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  Big data from single and multiple stars

   Faculty of Engineering and Physical Sciences

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  Dr Robert Izzard  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The 21st century is where big data meets astronomy. Grand surveys, like ESA's Gaia, already provide us with unprecedented data on every type of star in our Galaxy and beyond. Others, like SDSS and GALAH, give chemical information about these stars, critical evidence that probes their evolution. Others still, such as Pan-STARRS, detect transient phenomena such as supernovae and stellar merging. Given all this information, how do we best link it to our modelling of the stars and hence our understanding of fundamental astrophysics? In Surrey, we develop models of not just single, but also binary and triple stars using our binary_c stellar population nucleosynthesis framework. Recent developments include a standardized method for producing stellar population statistics, ready to compare population models directly to Gaia data using our new Python interface. What we lack are the tools to do the statistical comparison quantitatively and efficiently. This project aims to develop these tools, provide them for the astronomical community and use them to pin down uncertain processes in single and multiple-star evolution, like the all-important common-envelope evolution efficiency that governs the number of type Ia supernovae and merging neutron star–black hole systems.

Studentship group name

Surrey Institute for People-Centred AI


School of Maths and Physics

Research group(s)

Astrophysics Research Group

How to Apply

Open to UK and International students starting in October 2023.

Applications should be submitted via the Physics PhD programme page. In place of a research proposal you should upload a document stating the title of the projects (up to 2) that you wish to apply for and the name(s) of the relevant supervisor. You must upload your full CV and any transcripts of previous academic qualifications. You should enter ’Faculty Funded Competition’ under funding type.


The studentship will provide a stipend at UKRI rates (currently £17,668 for 2022/23) and tuition fees for 3.5 years. An additional bursary of £1700 per annum for the duration of the studentship will be offered to exceptional candidates.

Computer Science (8) Mathematics (25) Physics (29)
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 About the Project