During this project, data from Gaia, LSST, WEAVE, 4MOST, and S5 will provide the richest dataset to date for studying perturbations to stellar streams. The successful candidate will work on multiple facets of this problem. First, they will explore how perturbations to streams develop from a variety of baryonic effects. This catalogue of perturbed streams will be used to test how well subhaloes can be inferred, and which streams in the Milky Way are the cleanest detectors. Second, working with collaborators to exploit upcoming datasets, we will identify the most promising streams with perturbation signatures and fit these. For these fits, we will explore the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use similar techniques to make a statistical inference of the population of subhaloes by reproducing the stream's statistical properties.

The role will involve:

• building a census of simulated streams with a variety of perturbations;
• comparing CPU and GPU codes for generating and perturbing streams;
• using likelihood-based and simulation-based inference techniques for exploring subhalo properties;
• measuring the properties of subhaloes in the Milky Way;
• publishing results in leading journals and presenting the work at national and international meetings;
• contributing to the S5, LSST, WEAVE, and 4MOST collaborations where appropriate;
• contributing to the wider research culture of the Astrophysics Research Group at Surrey.

The successful candidate will be encouraged to develop their own research ideas within the broad themes of the project and to build an independent research profile.

About you

You will have:

• a PhD in astrophysics, physics or a closely related discipline;
• experience with research in Galactic Dynamics;
• programming experience relevant to scientific research;
• the ability to communicate research clearly through written work, presentations and collaboration;
• a track record of research outputs appropriate to your career stage;
• the ability to work both independently and as part of a collaborative research team.

We recognise that candidates come from a range of research backgrounds. We are looking for candidates with strong quantitative and computational skills who are excited to develop expertise in stellar streams as part of the project.

How to apply

Applications should be submitted online via the University of Surrey jobs portal. Please include:

• a CV, including a list of publications;
• a cover letter explaining your interest in the role and how your experience fits the project.

Interviews are expected to take place in early August and will be online.