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Potential PhD Topics

PhD Supervisors

Below are listed those CAS staff who may be currently looking for PhD students.

PhD Projects

Prof. Matthew Bailes

Prof. Chris Blake

Dr. Michelle Cluver

A.Prof. Jeff Cooke

  • No projects offered at this time

Prof. Darren Croton

Dr. Adam Deller

A.Prof. Alan Duffy

Dr. Deanne Fisher

A.Prof. Chris Fluke

Prof. Duncan Forbes

Prof. Karl Glazebrook

Prof. Alister Graham

Prof. Jarrod Hurley

Dr. Glenn Kacprzak

Prof. Virginia Kilborn

  • No projects offered at this time

Dr. Glen Mackie

  • No projects offered at this time

Prof. Sarah Maddison

Prof. Jeremy Mould

Prof. Michael Murphy

A.Prof. Emma Ryan-Weber

  • No projects offered at this time

Dr. Edward N. Taylor

Project Descriptions

The following set of projects have guaranteed external funding:

Mapping the Universe with Fast Radio Bursts

Supervisors: Prof. Matthew Bailes and Dr. Adam Deller

Fast Radio Bursts (FRBs) are intense, millisecond-long bursts of radio energy that originate from outside our own Galaxy. To date, just a single FRB has been localised to a host galaxy, meaning we have little idea about the nature of FRB progenitors. The upgrade of the Molonglo radio telescope to "UTMOST-2D" will provide the first dedicated FRB search capable of pinpointing bursts to arcsecond precision and identifying their host galaxies. By comparing the FRB "dispersion" (which measures of the number of electrons between the source and the Earth) to the host galaxy redshift, the FRBs detected by Molonglo can directly measure the density of the intergalactic medium and be used as a cosmic ruler to map the Universe.

This PhD project will involve analysing the population of FRBs detected by UTMOST and making and analysing multiwavelength follow-up observations those pinpointed by UTMOST-2D. Optical identification and spectroscopic characterisation of the host galaxies will be supported by radio continuum, optical, and X-ray searches for afterglow signals, as well as population analyses. The student will join the UTMOST collaboration under the joint supervision of Prof. Matthew Bailes and Dr. Adam Deller.



Unearthing FRBs using machine learning

Supervisor: Dr. Adam Deller

Fast Radio Bursts (FRBs) are radio signals originating in distant galaxies, generated by a source that is compact enough to switch on and off within milliseconds, yet powerful enough to be visible across billions of light years. As a source class, they are barely a decade old; their origins and the extent to which they can be used as astrophysical tools remain open questions. Answering these questions requires us to find as many FRBs as possible, with a low latency that enables the raw FRB data to be saved. However, at Earth we receive a corrupted impression of the original burst: dispersed and scattered by the intervening ionised plasma, and superimposed with radio frequency interference. Traditional FRB detection tools miss a substantial fraction of real bursts, while inundating the observer with false positives. Powerful machine learning alternatives such as convolutional neural networks are well suited to combine the tasks of identifying potential FRBs and classifying them as likely real or likely spurious, resulting in a higher detection rate while also providing lower latency. This project will focus on the development of cutting edge machine learning tools that are deployed on GPU hardware to facilitate improved FRB recovery rates at the three major Australian FRB finding telescopes: UTMOST, ASKAP, and Parkes.

Image caption: An FRB detected at the UTMOST telescope using traditional detection + classification methods. The two-dimension plot shows radio power as a function of time and frequency, with the dispersive sweep imposed by the ionised medium clearly visible. The top panel shows power as a function of time after correcting for dispersion and summing across frequency: the 'tail' of scattered power is now also clearly visible.



Time and Tide: Galaxies on the Move

Supervisors: Dr. Michelle Cluver

Galaxies in the local universe are rarely isolated, preferring to live in groups of varying sizes and densities. These associations experience a range of dynamical processes and interactions. But how does being in a group impact the star formation evolution of the member galaxies, if at all? Previous studies come to conflicting conclusions (e.g. Rasmussen et al. 2012, Ziparo et al. 2013, Wijesinghe et al. 2012, Schaefer et al. 2017), motivating the need for larger studies at low redshift combined with multiwavelength measures and accurate environmental measures.

This project will combine spectroscopic information from the Taipan galaxy survey and imaging from the KiDS (optical), VIKING (near-infrared), WISE (mid-infrared) and H-ATLAS (far-infrared) surveys towards investigating the significance of environment on the evolution of grouped galaxies. Missing from previous studies, we aim to include neutral gas (HI) observations from the SKA Pathfinders, MeerKAT and ASKAP, a key ingredient to star formation and a unique tracer of galaxy interactions. This will allow us to study the physical processes transforming galaxies from star-forming to quenched, as well as the short and long term effects of environment on star formation.

Hunting Ghost Galaxies

Supervisors: Prof. Duncan Forbes, Prof. Warrick Couch and Dr. Anna Ferre-Mateu

In 2015 a new class of galaxy was discovered - the ghostly Ultra Diffuse Galaxy (UDG). Such galaxies have the same total luminosity as a dwarf galaxy but a halo of dark matter similar to that of a giant galaxy. Some are 99.99% dark matter! Since their discovery they remain a mystery and a challenge to theories of galaxy formation. This PhD project aims to discover more UDGs from deep imaging, determine their stellar population and dynamical properties, and compare them with the latest theoretical models. This project is an observational one, using new data from the world's largest telescope and involving colleagues in California.


How does dark matter shape the lives of galaxies?

Supervisors: Dr. Edward N Taylor

The big question at the heart of this project is: how do the global properties of a galaxy (e.g. its size, shape, star formation rate, etc) connect to the properties of the larger dark matter halo that it lives in? The only way to really answer this question is observationally, and the best observational avenue to measuring galaxy-scale dark matter halos is by exploiting the physical phenomenon of gravitational lensing. The problem is that the effect is subtle, and we have to combine (or 'stack') weak lensing measurements of many hundreds or thousands of individual galaxy lenses in order to extract a meaningful signal. In this way, what we can do is to measure the mean halo properties, averaged over some set of (hopefully) similar galaxies.

The basic idea with this project will be to explore variations in halo masses, shapes, and sizes, as a function of galaxy properties. We want to answer questions like: all else being equal, do star-forming galaxies live in more or less massive halos than non-star-forming galaxies? What about disks versus ellipticals? Or as a function of galaxy radius? The key to this project is being clever in how we identify and construct the lensing galaxy samples: we will start by using existing data from the Sloan Digital Sky Survey, and quickly move to using new data from the Taipan galaxy survey. This will increase the effective size of our lensing sample by 4 and then by 10 compared to what is possible now, which translates directly into a better ability to split lens samples according to galaxy mass, size, shape, etc. In particular, by showing what galaxy properties correlate with halo mass, we can shed new light on the role that the dark matter halo plays in shaping the lives of galaxies.


Mapping electromagnetism's strength throughout the Milky Way with solar twin stars

Supervisor: Prof. Michael Murphy

The constancy of nature's laws, characterised by the fundamental constants, has been mapped out on all size-scales, from the laboratory through to the cosmic microwave background at redshift z=1100, except for one important size-scale: our own Milky Way galaxy. This project aims to make the first check on electromagnetism's strength in our Galaxy with high enough precision that a discovery of variation is possible (i.e. not already ruled out by previous, much less precise measurements). The idea is to use the spectra of solar twins – stars with spectra indistinguishable from our Sun's, and each other – as the probe because this allows for a highly differential measurement that will be immune to all manner of systematic effects that have precluded such a measurement in the past.

Depending on the status of this field at the time, there are both observational and theoretical avenues open for this position. For example, the student may either be making the first measurements on existing solar twin spectra, contributing to an effort to identify very distant solar twins, analysing new spectra of these distant solar twins, or making measurements with them. The new spectra would be taken with a new instrument on the 8-metre Very Large Telescope in Chile. Or they may be using advanced quantum mechanical calculations to determine how solar twin spectra depend on fundamental constants. These and other options will be discussed with the candidate.


Machine Learning for discovering High-Redshift and Exotic Objects

Supervisor: Prof. Karl Glazebrook

The forthcoming launch of the James Webb Space Telescope (JWST) will dramatically open up the possibilities for object discovery in the z>4 Universe. Dozens of imaging bands from 2-28 microns will suddenly become available, and sensitive enough, to find diverse types of early galaxies, and potentially new populations of exotic objects that may appear in the early Universe. Traditional colour selection (2-3 bands) is not optimal for this new data, and traditional photo-z selections requires highly specific models of what to look for. This PhD will develop machine learning techniques (e.g. convolutional and adversarial neural networks), optimised for datasets of 30-40 bands, for quickly identifying high-redshift galaxies and/or exotic objects (‘unknown unknowns’) using a mixture of empirical and simulated training data. This methodology will be developed using existing surveys such as ZFOURGE, 3DHST and ULTRAVISTA with the ultimate goal of building a software system optimised for JWST.


The nature of the first stellar populations in the Universe

Supervisor: Prof. Karl Glazebrook

The James Webb Space Telescope (JWST) is a 6.5m space telescope, significantly larger than the 27 year old 2.5m Hubble Space Telescope and will extend much further in to the infrared due to its cold location, one million km from the Earth. This will lead to new discoveries on topics such as the Initial Mass Function (IMF), rate of formation, elemental abundances and the presence of exotic populations. These studies will probe the fundamental physics of galaxy formation at z>4 in detail previously not possible. Recent discoveries of massive evolved galaxies (stellar masses >10^11 Msun) in such an early Universe point to an epoch of extremely fast star-formation followed by just as rapid quenching. A variety of next generation spectral synthesis codes have been developed in the past few years which allow more sophisticated treatment of emission lines, binary populations, abundances, complex star-formation histories and the IMF. In this PhD we will integrate these codes to study the stellar populations of the most massive galaxies and develop new algorithms to accelerate the modelling process. We will apply this to variety of ground-based surveys, and put in place a framework which we will use to study the millions of high-quality spectra expected from JWST.


Gravitational Wave Astrophysics

Supervisors: Prof. Matthew Bailes, Prof. Jarrod Hurley

Only 3 years ago the first gravitational waves were detected from a pair of coalescing black holes. This signalled the dawn of a new era in astronomy, that of gravitational wave astrophysics. Since then, many pairs of relativistic objects have been seen to enter a death spiral, including a pair of neutron stars. In this project the student will use the latest gravitational wave data coming from the Advanced LIGO and VIRGO interferometers to explore this new relativistic universe by using advanced parameter estimation techniques on the OzSTAR supercomputer to infer the underlying population of sources, and relate these to their progenitors, the OB stars, and the relativistic binary pulsars in our own galaxy. The student will join the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav) and have opportunities to work with its national and international partners.


The following set of projects are subject to a competitive allocation process where only a limited number of scholarships are available:

Understanding How Circumgalactic Gas Drives Galaxy Evolution

Supervisors: Dr. Glenn Kacprzak, Dr. Nikole Nielsen and Prof. Michael Murphy

Cool gas (green) from cosmic filaments accretes onto
the galaxy, which drives its rotation and controls the rate at
which it forms stars. Star formation and supernovae expel
gas back into the circumgalatic medium (purple). Background
quasars are used to study these gas flows around galaxies.

Ever wonder why some galaxies form stars while others do not? Or where does all the fuel for star-formation come from and what regulates it? The evolution of galaxies is intimately tied to their gas cycles - the gas accretion, star formation, stellar death and gas expulsion. As galaxies evolve, their gas cycles (known as feedback), give rise to an extended gaseous halo surrounding galaxies. Understanding how feedback works has become recognised as THE critical unknown process missing to fully understand galaxy evolution. Therefore, gaseous galaxy halos are the key astrophysical laboratories harbouring the detailed physics of how galactic feedback governs galaxy evolution.

Observationally, galaxy halos are studied with great sensitivity using quasar absorption lines. Imprinted on the quasar spectrum are the motions, chemical content, density, and temperature of the gas. These absorption signatures provide details that are unobtainable using any other method of observation. Here, the student will join an international collaboration and will examine how the host galaxy properties are linked to their circumgalactic gas properties using Hubble Space Telescope and Keck Telescope data.


An up-close view of extremely gas rich, turbulent disk galaxies

Supervisors: Dr. Deanne Fisher

The top row shows Hubble images of 3 of the turbulent disk galaxies from
the DYNAMO survey. The bright knots in each of these images represent
individual star forming regions with more star formation activity than
entire galaxies, such as in the Milky Way. The student will use data
from Hubble and ALMA (both shown on the bottom row) to study the details
of this “clumpy mode” of star formation, the most important mode of star
formation in the Universe.

Over 80% of stars in the Universe were formed in galaxies 10 billion years ago. These galaxies were marked by drastically high densities of star formation, were super rich in gas, and show evidence of widespread turbulence. Because these galaxies are so different from those galaxies in the local Universe, we cannot assume that local theories of star formation robustly explain such extreme environments. However, these galaxies are also very distant from us. We therefore cannot resolve the star forming regions. This situation has created a very large problem for galaxy evolution: We do not currently understand star formation processes in the most important epoch of galaxy evolution in the history of the Universe.

Our group has mined datasets of hundreds of thousands of galaxies to find a set of rare galaxies in the local Universe which are very closely matched to conditions in galaxies 10 billion years ago. This PhD project will study the properties of these galaxies to determine the stellar mass, stellar populations, star formation rates and gas masses of these massive complexes of star formation found inside nearby turbulent, gas rich galaxies (called the DYNAMO sample). This project has recently been awarded time on Hubble Space Telescope, the Atacama Large Millimeter Array (ALMA), as well as having data from programs with Hubble, NOEMA and Keck. Analyzing data from these exciting telescopes will be the basis of the PhD project.


Measuring the masses of galaxies from starlight and dynamics

Supervisors: Dr. Edward N. Taylor

Galaxies are observed as collections of stars - but we also know that these stars reside at the centre of much larger and much more massive halos of dark matter. Current thinking is that these dark matter halos not only seed the initial formation of the galaxy, but also drives and regulates most of the physical processes associated with the ongoing evolution of galaxies. The observational challenge is to try to connect the properties of real galaxies in the real universe to the mass distribution for dark matter halos that we expect from cosmology. The overarching goal of this project is to do just that: to determine how the combined mass of stars within a galaxy is related to its total mass (including dark matter) or, in other words, to measure the stellar-to-halo mass relation for galaxies in the local universe.

This project will use new data from the Taipan galaxy survey. Covering half of the celestial sphere - the entire Southern sky - Taipan will be the world's widest galaxy redshift survey, and aims to measure redshifts and distances for ~2 million galaxies. When it starts survey operations in 2019, the Taipan facility will operate fully automatically, and will take about 360 spectra per hour, all night, every night. (And a planned upgrade in late 2019 will more than double the survey speed!) There are great opportunities to spend time at the telescope for this project. There are also plenty of opportunities to work closely with the Taipan cosmology teams, as well as other large scale Australian survey teams including Wallaby, Emu, Hector, and others.


Testing the cosmological model with the Taipan Galaxy Survey

Supervisors: Prof. Chris Blake

One of the most fundamental tasks facing astronomers is to determine the cosmological model describing the physics of the expanding universe, in terms of its matter-energy content and the laws of gravity. Recent observations of the universe show that our current understanding of the relevant physics is profoundly incomplete, forcing cosmologists to invoke a mysterious dark energy, that propels an apparent acceleration in the present-day cosmic expansion rate.

The Taipan Galaxy Survey is a new Australian-based project that will measure redshifts for 1,000,000 galaxies and peculiar velocities for 100,000 galaxies, mapping out the large-scale structure of the local Universe. The resulting dataset will yield the most precise direct measurement of the present-day expansion rate of the universe, the largest maps of the density and velocity fields of local structures, and new and stringent tests of large-scale gravitational physics using galaxy motions, probing Einstein’s theory of gravity and alternatives. The full set of scientific goals for the survey is described in this paper.

Depending on the skills and interests of the student, this project could involve a focus on observations, data analysis or theory within a key science investigation in the project.

Picture caption: The UK Schmidt Telescope at Siding Spring Observatory, where the Taipan Galaxy Survey will take place


Galaxy Structure and massive black holes

Supervisors: Prof. Alister Graham

Artist's impression of a black hole. Credit: James Josephides.

This project will explore how stars are distributed in galaxy images obtained from both ground-based telescopes and satellites such as Hubble and Spitzer. The structure of galaxies reveals much about how they formed, how they are connected with one another and also with the massive black holes that reside in their cores. A feeling for the type of research done with Prof. Graham can be seen in his Press Releases.


Testing planetesimal collision models with debris disk observations

Supervisors: Prof. Sarah Maddison

Testing planetesimal collision models with debris disk observations: Planets form through the collisions of asteroid-like bodies. The only way to see these large bodies is via the dust grains they produce via collisions. The student will join an international team conducting the PLATYPUS survey with the Australia Telescope Compact Array to study intrinsic properties of debris disks and test predictions of collisional models of planetesimals.


Weighing the Universe with Deuterium

Supervisors: Prof. Michael Murphy and Dr. Glenn Kacprzak

This project aims to weigh the universe (i.e. measure the number of baryons it contains) by comparing the amount of hydrogen and its main isotope, deuterium, in distant, almost pristine clouds of gas. The baryon fraction is a fundamental quantity in cosmology, so obtaining new measurements using deuterium is essential for detecting any departures from our standard cosmological model. We observe these gas clouds in the spectra of background quasars – the super-bright accretion discs around supermassive black holes – taken with the largest optical telescopes, such as the Keck 10-metre in Hawaii and VLT 8-metre in Chile. Cases where an accurate (and precise) measurement can be made are incredibly rare, but we have identified several new examples that will provide competitive baryon fraction measurements. The aim is to analyse these existing spectra, and obtain new spectra if required, and test the standard cosmological model.

This is a collaboration with astronomers in the US (Vermont & California) and travel to work with these collaborators is foreseen. Observations using either the Keck and/or VLT are also likely during the course of the PhD project.


The distribution of gas and metals around galaxies, from low to high redshift

Supervisors: Prof. Darren Croton

The hydrogen gas content of a galaxy, from which new stars form, is an excellent probe of its future, while the metal content within that gas, produced in supernova during the death of old stars, is a similarly valuable probe of its past. The goal of this project is to make predictions for the distribution of gas and metals around galaxies from low to high redshift, for different galaxy types and in different environments, and compare these against observations. The project has 5 parts: (1) undertake a literature review of our current understanding of gas and metals in galaxies; (2) to review the theory of how galaxies form and evolve across cosmic time, with a focus on the relevant physical processes; (3) to construct a new model universe with the existing SAGE galaxy formation model on the OzStar supercomputer at Swinburne; (4) using this model, to reproduce the current observations of gas and metals in and outside of galaxies out to the redshifts for which it’s been measured; and (5) explore the model beyond this baseline to make predictions for future observational surveys. Additional goals will be to develop a solid understanding of galaxy evolution and cosmology, become familiar with supercomputer simulations and models, and the technical skills required to create and use them for science. This project will involve collaboration with international partners in the US, Europe and Japan.


Dark Matter Visible

Supervisors: Assoc. Prof. Alan Duffy

There exists an unknown invisible mass in the Universe, outweighing everything we can see five times over. This mysterious substance is called Dark Matter, non-interaction with electromagnetism makes it both challenging to directly observe or detection as it is therefore nearly collisionless. Astronomical observations have confirmed the large-scale distribution of dark matter but to determine the particle nature will require measurements on light year scales or event direct detection of the particle itself. Confirming the nature of this new particle is one of the greatest scientific endeavours of our century. Swinburne is part of SABRE, a new experiment one-kilometre underground at a gold mine in Stawell, which will attempt to detect this dark matter.

This project will use high-resolution simulations of Milky Way-like galaxies to explore the potential properties of the dark matter near the Sun's orbit and which SABRE may detect. It will also generate distributions that can inform indirect detection efforts such microlensing, self-annihilation signals and perturbations to the visible sector. A series of zoom-in hydrodynamical simulations of Milky Way type galaxies have been created on the largest supercomputers in the world. Along with these simulations is a new technique to be developed in collaboration with Caltech’s Prof Phil F Hopkins on a more robust numerical estimate for small scale dark matter structures. This research efforts will be used to generate an expectation for the range of dark matter distributions that can inform direct detection experiments. A background/masters in numerical simulations (esp. Gadget/GIZMO) is an advantage as is experience in Python or C.


Microlensing Detection of Primordial Black Holes

Supervisors: Prof. Jeremy Mould and Assoc. Prof. Alan Duffy

We aim to measure the fraction of the dark matter in our Galaxy in the form of substellar mass primordial black holes (PBH). If they exist, such objects brighten background stars when they pass between the star and Earth. This is called gravitational microlensing. Astronomical camera technology now allows a microlensing experiment in our Galaxy's halo to decrease the detected event time to ~10 seconds from its limit in the MACHO experiment two decades ago of ~1 day, reaching PBH of a billionth of a solar mass. Expected outcomes include the mass range and density of these objects in the Galaxy. If this is not a detection but an upper limit, it will redirect the search for a quarter of the mass of the Universe towards other candidates.


The dynamics and excitation of circumnuclear disks in southern Seyfert galaxies

Supervisor: Prof. Jeremy Mould

According to Active Galactic Nucleus (AGN) unification schemes, a black hole is hidden by an optically and geometrically thick dust torus. Just outside this central region inflows and outflows of gas, fuelled by and fuelling star formation, determine the activity of everything within. The time is right to survey a complete sample of nearby southern narrow line Seyferts to (1) characterize the dynamics of these circumnuclear disks as a function of galaxy mass and (2) outline the ecology of the gas flows that support them. First with the NTT we need to see which of Chen et al’s complete sample of nearby narrow line Seyfert galaxies have emission lines in the 1–2μ windows and are thus amenable to NIR adaptive optics (AO) IFU observations. VLT IFU observations with laser guide star AO will then enable the study of a complete sample.


A bottom heavy mass function in massive galaxies

Supervisors: Prof. Jeremy Mould and Prof. Duncan Forbes

A mass function rich in low mass dwarf stars can be diagnosed unambiguously with high signal-to-noise near infrared spectra, as we have shown recently with high resolution population synthesis models. A correlation between initial mass function slope and central velocity dispersion, σ, has been shown with 90% confidence to be present in our initial small sample of early type galaxies. To remove any uncertainty, we would like to triple this sample. This is a necessary step towards a fuller survey in which correlations with stellar population parameters σ, Z and α/Fe can be reliably separated.


Astronomical knowledge discovery beyond the petascale

Supervisors: A.Prof. Chris Fluke

As astronomy moves ever closer to the Square Kilometre Array's exascale data era, an increasing number of existing desktop-based workflows will fail. Instead, astronomers will turn to automated processing using dedicated high-performance computing resources coupled with advanced data archives. Yet the ability to look at the most important data is crucial. In this project, you will research, design, implement and evaluate new visualisation-based knowledge discovery approaches. The goal is to support interactive, multi-dimensional analysis of data from observations, simulations, model fits and empirical relationships. The research will require an investigation into methods for combining visualisation-directed model-fitting with emerging machine learning techniques - such as Deep Learning - to enhance and accelerate the path to discovery. A key focus will the WALLABY survey of extragalactic neutral hydrogen with the Australian Square Kilometre Array Pathfinder (ASKAP), however, the techniques developed will be suitable for a range of current and future data intensive programs - within and beyond astronomy. All stages of the project will utilise Graphics Processing Units (GPUs) as computational accelerators. The student will also have access to Swinburne University’s Advanced Visualisation facilities: the Enhanced Virtual Reality Theatre and the Swinburne Discovery Wall. This project will suit a student with existing strong programming skills, and interests in GPU-computing and/or data-intensive discovery


The Three Rs of Astronomy

Supervisor: A.Prof. Chris Fluke

Augmented (AR), Virtual (VR) and Mixed Reality (MR) technologies -- the Three Rs -- are now commonplace in entertainment and education. However, if their potential is ever to be realised as part of the astronomer's daily research workflow, the barriers to adoption need to be lowered or removed. In this project, you will research, develop, test and evaluate highly-customisable visualisation and analysis workflows with AR/VR/MR that support astronomers in making, communicating, and publishing discoveries. Of critical importance is the need to create easy-to-use workflows integrating with online datasets, so that astronomers can focus on their data rather than programming for a specific head-mounted device. A set of target application areas in astronomy will be selected based on student's interests and research priorities within the Centre for Astrophysics & Supercomputing. This project will involve collaboration with Swinburne researchers in the field of Interactive Media, and may provide opportunities to contribute to industry-focused research (through Swinburne's Advanced Visualisation Laboratory). This project will suit a student with strong technical and programming skills. Previous experience with Unity or Unreal Engine is beneficial but not essential.