Understanding exoplanets and their host stars using large data sets and AI

The possibility of planets orbiting other stars has been a topic of fascination for centuries. We are the first generation that has brought these planets - now known as exoplanets - from the realm of science-fiction into that of science. An important milestone was the discovery of several planets orbiting a pulsar (Wolszczan & Frail, 1992), followed by the first planet orbiting a star more similar to our Sun (Mayor & Queloz, 1995), an achievement awarded the 2019 Nobel Prize in Physics.

The 25+ years since have been filled with an abundance of exciting discoveries and today we know over 5000 exoplanets. These planets exhibit an incredible diversity of properties. Why do so many planets have tiny orbits - often much smaller than that of Mercury?

What causes planets to become rocky, gaseous, or something in between? Why do some planets have orbits that are strongly eccentric, or misaligned with the rotation of their host stars? What happens to planets when stars evolve away from the main sequence?

Which planets are the most favourable and interesting targets for studies of their atmospheres? How unique is our solar system - are we alone?

Exoplanet science is a young field of research and there is great potential for many ground-breaking new discoveries. A PhD project is available that will seek to link the discovery of thousands of exoplanets to planet formation models. In particular, a key ingredient to understand the properties of exoplanet systems is the stars around which they orbit.

In this project, we will attempt to link stellar properties, such as the planet birth environment and the stellar age, to the architecture of planetary systems. To do so we will use state-of-the-art statistical techniques, ranging from Bayesian modelling to machine learning and AI. The successful student will have the opportunity to shape the direction of the project.