Computational project taking advantage of big data from large surveys like ESA's Gaia, SDSS, Galah and Pan-STARRS.

Funder	Science and Technology Facilities Council
Recipient Organization	University of Surrey
Country	United Kingdom
Start Date	Sep 30, 2022
End Date	Mar 30, 2026
Duration	1,277 days
Number of Grantees	2
Roles	Student; Supervisor
Data Source	UKRI Gateway to Research
Grant ID	`2780144`

Grant Description

The successful candidate will model single, binary and triple stars using a stellar population nucleosynthesis code and implement statistical tools to make comparisons with Gaia and other big data. One big aim is to pin down uncertain

processes in single and multiple-star evolution, like the common-envelope evolution efficiency that governs the number of type Ia supernovae and merging neutron starA black hole systems.