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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

  • No projects offered at this time

Prof. Chris Blake

  • No projects offered at this time

Dr. Michelle Cluver

  • No projects offered at this time

A.Prof. Jeff Cooke

Prof. Darren Croton

  • No projects offered at this time

A.Prof. Adam Deller

Prof. Alan Duffy

A.Prof. Deanne Fisher

  • No projects offered at this time

Prof. Chris Fluke

Prof. Duncan Forbes

  • No projects offered at this time

Prof. Karl Glazebrook

Prof. Alister Graham

Prof. Jarrod Hurley

  • No projects offered at this time

A.Prof. Glenn Kacprzak

  • No projects offered at this time

Prof. Virginia Kilborn

  • No projects offered at this time

Dr. Glen Mackie

  • No projects offered at this time

Prof. Sarah Maddison

Prof. Jeremy Mould

  • No projects offered at this time

Prof. Michael Murphy

  • No projects offered at this time

A.Prof. Emma Ryan-Weber

  • No projects offered at this time

Dr. Ryan Shannon

  • No projects offered at this time

A.Prof. Edward N. Taylor

Project Descriptions

The following set of projects have guaranteed external funding:

The missing population of intermediate mass black holes

Supervisor: Prof. Alister Graham

There is a largely-missing population of intermediate-mass black holes (IMBHs) with masses higher than that formed by single stars today (Mbh=1.4 to 120 MSun) and less massive than the supermassive black holes (SMBHs: 105—1010 MSun) known to reside at the centres of big galaxies.  Not surprisingly, astronomers around the world are hotly pursuing the much-anticipated discovery of IMBHs.  This thesis will involve several interconnected projects involving telescope and satellite image analysis and statistical techniques.  Improved methods for estimating both IMBH and SMBH masses will be developed and applied, with ties to the upcoming Large Synoptic Survey Telescope expected.  The coexistence of these massive black holes in dense, compact star clusters at the centres of galaxies is also expected to be a source gravitational radiation detectable by the planned eLISA satellite, for which updated predictions will be made.

Students will benefit from membership in the ARC Centre of Excellence for Gravitational Wave Discovery, OzGrav.


Localising fast radio bursts with the Australian Square Kilometre Array Pathfinder

Supervisor: Dr. Ryan Shannon

Fast radio bursts are an enigmatic population of transient astronomical events that are promising to be a revolutionary astrophysical tool. The bursts are exciting because they both represent a brand new and unprecedentedly bright class object and are now demonstrating the ability to uniquely probe the cosmology of the Universe. This project will utilize the wild field of view of the Australia Square Kilometre Array Pathfinder (ASKAP) to rapidly increase the population of the bursts and identify hosts, emission mechanisms and explanations for the bursts. ASKAP has proven itself to be a reliable FRB detection machine and localization machine, able to pinpoint burst locations to within galaxies.

Your project, which would be undertaken as part of the CRAFT collaboration could include:

  • Developing methods and pipelines to detect bursts in real time.
  • Developing techniques to accurately pinpoint bursts.
  • Studying the demographics of the burst population, and synthesizing with discoveries made as part of other projects.
  • Understanding the magnetionic properties of the intergalactic medium and host galaxies for FRBs.
  • Coordinating multi-wavelength campaigns to identify hosts and counterparts to the bursts.
  • Searching for galactic analogues to FRBs through a galactic plane single pulse surveys.

    Specific contributions will depend on your interests. In addition, you will also gain hands-on experience with ASKAP. Through all the of the Ph.D. you will gain experience with computation and signal processing while doing cutting-edge astrophysics.


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

    Imaging and modelling the aftermath of gravitational wave mergers

    Supervisor: A.Prof. Adam Deller

    This project aims to capitalise on the dawn of the era of gravitational wave astronomy by studying the radio afterglows that result from gravitational wave merger events in minute detail.  When two compact objects (one neutron star plus a second neutron star or a black hole) merge, a burst of gravitational wave emission is released, and a violent outflow is launched that can lead to pan-chromatic electromagnetic emission.  By studying the radio emission of the outflowing material, we can determine both the characteristics of the outflowing material, and the viewpoint from which we are seeing the system.  Twin inputs are required: 1) ultra-high resolution radio images obtained with intercontinental radio interferometers, and 2) highly sophisticated computational models of the merger.  To date, this has been performed for just one system, the famous NS-NS merger GW170817, for which our team showed that the merger launched a powerful and narrowly collimated jet of material (Mooley, Deller, et al., Nature, 2018).  In the near future, as LIGO/Virgo detects many more NS mergers, we anticipate applying these techniques to an increasing sample of systems, recovering information about the merger events that cannot be obtained from the gravitational wave data alone and also improving on "standard siren" measurements of the expansion of the Universe.   The successful candidate will work with A/Prof Adam Deller and an ARC-funded postdoctoral researcher, along with international project partners at Caltech and Tel Aviv University, focusing on the comparison between radio interferometry data and hydrodynamical models to extract physical parameters of the merger afterglow.

    Image caption: Model (left) and VLBI data (right) of the radio afterglow of the NS-NS merger event GW170817 (Mooley, Deller, et al., Nature, 2018).  By comparing the VLBI data to a range of hydrodynamical and analytic models, we were able to constrain the viewing geometry of the system and the jet parameters.


    The Deeper, Wider, Faster program: Discovering the fastest bursts in the Universe

    Supervisor: A.Prof. Jeff Cooke

    The Swinburne-led Deeper, Wider, Faster (DWF) program is the first all-wavelength program designed to detect and rapidly follow up the fastest transients in the Universe, such fast radio bursts, supernova shock breakouts, all types of gamma-ray bursts, kilonovae, flare stars, and others, including the discovery of unknown classes.  DWF is the world's largest collaboration of telescopes, with over 60 major observatories on every continent and in space.  DWF coordinates wide-field radio through gamma-ray telescopes, such as Parkes, ASKAP, MeerKAT (radio), the South Pole Telescope (mm), CTIO DECam, Subaru Hyper-SuprimeCam (optical), NASA Swift, HXMT (X-ray), and HESS (gamma-ray), to observe the same target fields at the same time and processes the data in real-time either at the telescopes or using the Swinburne OzSTAR supercomputer.  Transients are identified within minutes of their outbursts in our Mission Control room at Swinburne that incorporates leading-edge data visualisation technology.  The fast identification of the transients enables rapid-response spectroscopic and imaging follow up observations before the events fade using the world’s largest telescopes, such as Keck in Hawaii, the VLT and Gemini-South in Chile, SALT in South Africa, the AAT optical and ATCA radio telescopes in Australia.  Finally, our network of over thirty 1-2 metre-class telescopes worldwide provide simultaneous and/or follow-up imaging and spectroscopy to monitor the events.

    The student will participate in the DWF coordinated observing runs and help analyse the data to produce leading transient science.  Depending on the interests and experience of the student, the project will involve (1) developing techniques to search the deep optical data to investigate known fast transients and potentially discover new classes of transients, (2) cross-matching multi-wavelength (radio, optical, UV, x-ray, and gamma-ray) data to extend our knowledge of fast transients and new event behaviour, (3) progressing real-time fast transient identification and predictive capabilities using machine and deep learning techniques, and (4) enhancing and accelerating transient discovery by progressing data visualisation and data sonification techniques, including virtual reality and augmented reality analyses.

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    Astronomical knowledge discovery beyond the petascale

    Supervisor: Prof. Christopher Fluke

    The immensity of data available to modern and future astronomers demands new approaches and techniques for analysis and visualisation. Astronomers are already turning to automated processing using dedicated high-performance computing resources and advanced data archives, supported by machine learning and artificial intelligence. Within this Petascale Astronomy Era, the ability to visualise data will still be crucial for quality control, decision-making, and to support new discoveries. PhD projects are available in one or more of the following areas:

    1. Visualisation Beyond the Desktop: Previous PhD projects have resulted in the development of solutions for real-time visualisation of Terabyte-scale volumes (GraphTIVA), comparative visualisation of volumetric data on a tiled display wall (encube), and advanced graphics shaders (shwirl). In this project, you will extend, combine, improve, and develop new visualisation solutions that support knowledge discovery in astronomy beyond the desktop -- including virtual reality, augmented reality, large-format displays, Gigapixel tiled displays, and cloud-computing services.
    2. Cyber-Human Discovery Systems: This project addresses the question "How do humans and machines work together most effectively to maximise the scientific return of data?" Cyber-human discovery systems combine human-centred visualisation with automated data mining, through strategies such as machine learning and artificial intelligence. At different stages of a discovery process, the amount of work performed by humans and machines can vary -- but this requires an increased understanding of what astronomers do. In this research, you will provide this understanding for a number of astronomical contexts, and create new solutions to support highly customisable, dynamic, visualisation solutions that will sense and enhance the capabilities of humans working closely with machines.

    These projects are expected to make use of Swinburne University's Advanced Visualisation facilities - the Enhanced Virtual Reality Theatre and the Swinburne Discovery Wall - and the OzSTAR Supercomputer. These projects will suit students with existing programming skills and interests in data-intensive discovery. Relevant astronomical applications will be selected, offering opportunities for students to collaborate with other researchers in the Centre for Astrophysics & Supercomputing.


    Finding Strong Gravitational Lenses in the High-Resolution imaging era

    Supervisors: Prof. Karl Glazebrook and A.Prof. Adam Deller

    Strong gravitational lens systems are a corner piece for the study of cosmology, dark matter and galaxy evolution. It has now been established that they can be found very efficiently using convolutional neural networks (a.k.a. 'deep learning') in ground based surveys, searching millions of sources to find hundreds of lenses. In this PhD project we will develop the next generation of machine learning techniques that will be able to detect strong lenses in future high-spatial resolution large imaging surveys. These include orbiting observatories such as Euclid and the Chinese Space Telescope which will survey thousands of square degrees in the optical at resolution similar to the Hubble Space Telescope, and forthcoming SKA and VLBI radio surveys which can deliver resolutions down to milliarcseconds for millions of sources. Key research probems to be addressed are: (i) simulate lensed galaxies at much higher spatial resolution in order to provide realistic training samples, (ii) simulate instrumental effects in the radio domain and (iii) will explore new techniques such as transfer learning and generative adversarial networks to build more adaptable systems.

    Image caption: Example of a very high-resolution images of a gravitational lens from Tamura et al. (2015). The thin arc in the RGB image is the cold dust emission from a lensed galaxy at z=3.042 as observed with ALMA in the sub-mm band at 30 milli-arcsecond resolution. The contours show the “low” resolution infrared data from the Hubble Space Telescope superimposed, showing this emission comes from a different part of the galaxy. The galaxy acting as the gravitational lens has been subtracted from this image.


    How does dark matter shape the lives of galaxies?

    Supervisor: A.Prof. 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.


    Dark Matter Visible

    Supervisors: 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.


    Simulating Warm Dark Matter

    Supervisors: Prof. Alan Duffy

    The current dark matter paradigm has been incredibly successful in creating the large-scale structure of the universe we see around us, with simulations explaining the distribution of galaxies across cosmic distances. If you zoom in on smaller scales the simple ‘cold dark matter’ model of a massive particle that has effectively no thermal velocity begins to struggle to explain what we see. From cusp vs core tensions of the inner densities to the missing satellite problem there would appear to be only two options: complex astrophysical processes dramatically alter the dark matter structure on small scales, and / or the dark matter is in fact not perfectly collisionless and ‘cold’, instead it is either self-interacting or has some internal thermal velocity – known as warm dark matter.

    Creating the simulations to explore warm dark matter are fraught with numerical instabilities which cause immense difficulties in testing this theory. In this PhD we will explore a new, more rigorous mathematical framing of the theory that will allow us to finally test this highly compelling extension of the dark matter paradigm. Experience in mathematical modelling, python / C / C++ will be advantageous.


    Artist's impression of a black hole. Credit: James Josephides.
    Galaxy Structure and massive black holes

    Supervisors: Prof. Alister Graham

    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.