The student will upgrade an existing seismic classifier using modern machine learning techniques and expanded training sets.

You will use 3D magnetohydrodynamic simulations to model asymmetric accretion on protostars and their discs.

We are currently assembling a new supernova sample to constrain cosmology.

Redshifts are usually determined from the galaxies that host the supernovae, but some hosts are too faint. This project aims to improve the accuracy and precision of redshifts obtained from supernovae.

The student will process a database of sink-particle produced from 4pc^3 star cluster forming simulations to study how young binary and multiple stars evolve.

The DREAMS telescope is a 50cm class, wide-field, infrared telescope dedicated to the search of transient event. In this project we will work on developing its data reduction pipeline to increase the scientific output of the telescope and make it the ideal infrared complement to the Vera Rubin Observatory.

Are you ready to blend academic and commercial experience? Can you dive into details and also see the bigger picture? Are you interested in seeing how your knowledge can be applied to real-world outcomes? If so, we’d love to hear from you.

Do you enjoy working with instrumentation? Are you interested in using data to inform real-world decisions? Are you an independent thinker who loves to solve problems? If so, we’d love to hear from you.

We are searching for ways to improve supernovae as distance indicators using a new low-redshift sample of type Ia supernovae.

CSIRO has a cold spray research group which is developing cold sprayed Invar. This project will be developing an optical metrology setup to measure the creep of the cold sprayed Invar in collaboration with CSIRO Lab22 in Clayton, Victoria.

In collaboration with Omexom and the ACT Government, we are working on reducing light pollution in Canberra. This work involves aspects of using machine learning for monitoring, modelling population flows for automation, and looking at impacts on the environment as well cultural impacts.

This project aims use machine learning to identify and characterise these magnetic red giants in both the Kepler and TESS samples, cross match them with spectroscopic surveys such as APOGEE, and map their distribution, chemistry and motion across the Galaxy.

Modelling the oscillations of Red Clump stars using stellar evolution codes to study their internal structure.

This project will investigate the properties of binary neutron star progenitors and their host galaxies by applying state‑of‑the‑art transient modelling tools. By linking the astrophysical properties to their explosive counterparts, we will have a better idea of what types of sources will produce kilonovae. A deeper understanding of this astrophysics is essential for optimising future electromagnetic follow‑up strategies for gravitational‑wave detections.

The Physics of Supernovae: Using Observations to understand supernova progenitors, explosion energies, and nucleosynthetic production.

Supermassive black holes in the early Universe are more massive than we can presently explain. We aim to construct their demographics and reveal their origin.