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Vacation Scholarships in Astronomy at CAS

The Centre for Astrophysics & Supercomputing (CAS) accepts applications for Vacation Scholarships from enthusiastic university students with excellent scholastic records who are in the last, or second last, year of their undergraduate or Honours/Masters degree.

With 23 research faculty and more than 40 postdoctoral researchers and PhD students, CAS is a vibrant, friendly environment for studying most fields of astronomy. Swinburne astronomers have guaranteed access to the twin Keck 10-m Telescopes in Hawaii - the world's premier optical observatory - and CAS owns and operates one of Australia's most powerful supercomputers - Ozstar. We also develop advanced, immersive 3D data visualization facilities and create 3-D animations and movies promoting and explaining astronomy to the broader community.

Swinburne's Hawthorn campus is situated in a lively, urban setting just minutes by public transport from Melbourne's city centre.

Our Vacation Scholarship programme aims to provide undergraduate students with some insight into how exciting research is and how it is conducted. Students will join a research project, or possibly help start a new one, in one of the many areas of astronomy in which CAS staff and post-docs are experts. The various projects on offer are listed below. Projects can involve all aspects of astronomical research, from proposing or carrying out new telescope observations, to analysing data, to conducting theoretical calculations or advanced simulations. Many previous students have eventually published peer-reviewed research articles on some of their Vacation Scholarship research.

In 2020 this programme will run remotely and only be available to students at Australian universities. Projects are expected to run over 8 weeks, between November and February, with the timing to be negotiated between the student and their nominated supervisor. Vacation scholars are paid a tax-free stipend of $500 per week.

Applications are now being accepted and should be received before September 30; they should include the following:

  • A cover letter (see below for further information);
  • A copy of your official academic record, including an explanation of the grading system used;
  • Your Curriculum Vitae;
  • Any supporting documentation of previous research.

Applicants should also ask a lecturer or supervisor at their current university to send a letter of recommendation. This should be sent by the lecturer/supervisor directly; applicants should not include reference letters in their own application.

Applications and reference letters should be emailed to Dr. Michelle Cluver ( with the above information attached (preferably as PDF documents).

The cover letter is important and should
(i) set out why you are interested in undertaking a vacation scholarship at Swinburne and
(ii) list at least two research projects you are interested in working on (with an optional ranking). See below for the current list of projects on offer.

Potential Vacation Scholarship Research Projects

The following list outlines particular projects currently on offer. Other projects not listed here may also arise. If you have questions, contact Dr. Michelle Cluver at the above email.

(Last Updated 5-August-2020)

  • Asteroid mass primordial black holes
    Formed in the cauldron of the inflationary Universe, these objects are candidates for the 24% of everything that is Cold Dark Matter. They may have already been detected in our observing run this year on the Blanco 4m telescope, sister of the Anglo Australian Telescope. The student's job is to spend the summer finding them in our gravitational microlensing data. Your python skills will be handy, as we are using the Ozstar supercomputer to find these needles in our terabyte haystack.
    Supervisors: Prof. Alan Duffy and Prof. Jeremy Mould

  • Astronomical Machine Learning in the Cloud
    The aim of this project is to investigate techniques for deploying astronomical code, particularly machine learning models, to publicly accessible cloud resources for use by the astronomical community. Machine learning is becoming increasingly prevalent in astronomy, but there is no clear standard for making both models and data instantly available for members of the scientific community to use in research. This project will investigate some efficient ways to use cloud resources such as Amazon Web Services and Microsoft Azure to create resources on the fly and present an interface to scientists to instantly and conveniently make use a model. At the end of the project, the student will deliver the code to allocate resources and train and deploy models, and a brief report documenting the findings. This project would suit a student with strong computer skills (for example, familiarity with a Linux command line). Detailed knowledge of astronomy is not required.
    Supervisor: Dr Colin Jacobs

  • Gravitational waves from core-collapse supernovae
    Gravitational wave detectors have made the first discoveries of gravitational waves from binary neutron stars and binary black holes. As the detectors become more sensitive they will discover other sources of gravitational waves. One of those potential sources is a core-collapse supernova. Core-collapse supernovae are the explosive death of massive stars at the end of their lifetime, and are the birth place of neutron stars and black holes. Traditional gravitational wave searches use matched filtering. However, this search method cannot be used to search for gravitational wave signals from core-collapse supernovae as the phase of the signals are stochastic. In this project, you will develop a new search technique for core-collapse supernova gravitational wave signals and test the new method on data from the Advanced LIGO and Advanced Virgo gravitational wave detectors.
    Supervisor: Dr. Jade Powell

  • Can black hole binaries explain the strong optical emission lines in galaxies?
    X-ray binary stars are generally interacting binary systems in which one star is either a black hole or a neutron star. Due to mass transfer they produce x-ray emission and this high energy photons have long been thought to be one of the contributors to high energy optical emission lines observed in galaxies. With new integral field spectrographs, we can now perform spatially resolved studies in local galaxies to investigate if locations with such strong emission lines have corresponding x-ray detections. In this project, you will look into some of the public data from the ESO VLT/MUSE spectrograph and combine with X-ray source catalogues from the Chandra X-ray observatory to determine if such a correlation can be established.
    Supervisor: Dr. Themiya Nanayakkara

  • 3D foetal brain ultrasound: help brain development studies and improve prenatal clinical care
    The human brain is the most complex organ of the human body, and its link to human behavior, memory, decision making and consciousness is tantalizingly elusive. One key outstanding question in the study of the human brain is what healthy development looks as the brain is forming in utero, development that will give rise to the full complexity of the human experience. What is the extent of variability in what is considered healthy, and when does that variability veer into states that are associated with disease? This has huge implications not only for understanding human brain development, but also in foetal health monitoring throughout pregnancy. Early brain development in utero has been difficult to study because of a lack of tools. While ultrasound is the primary point of care tool for foetal health monitoring throughout pregnancy, it has not been widely adopted for scientific investigation of foetal brain development. The reason for this is routine clinical practice uses 2D ultrasound, but 2D slices of the brain does not allow accurate measurements and population studies. 3D ultrasound is preferred for scientific study, but there is a lack of standardised tools for analysing 3D foetal ultrasound brain data. Over the last decade, many software tools have been developed for processing and analysing 3D foetal ultrasound brain data by engineers and image processing experts, but access to said software and using it is outside the skill domain of medical researchers. You will work on creation of a software GUI toolkit that allows people without coding skills to use these tools, helping to make the use of 3D foetal brain ultrasound data for medical research pervasive. The tools you will include in this GUI were developed by the Oxford Ultrasound NeuroImage Analysis Group (
    Supervisor: Dr. Jielai Zhang

  • Dust in the Interstellar Medium: what is it like really?
    Dust is a critical component of the interstellar medium (ISM) and plays an important role in galactic evolution. It can serve as a catalyst for the formation of molecular hydrogen, heat the ISM via the photoelectric effect in the presence of UV light, help dense regions cool, and impart radiation pressure to gas. For those who do stellar or extragalactic observations, dust in the Milky Way is a source of extinction, and so must be characterized to measure the intrinsic color and brightness for a source of interest. For those who study cosmology, dust polarizes the signal coming from the cosmic microwave background (CMB), and so must be characterized to measure the polarization of the CMB due to cosmological effects. Suffice to say, understanding the physical and radiative properties of dust is a critical element in many areas of astronomy. However, measurements of the amount (column density) of gas and dust, as well as properties of the dust are very nuanced. Many parameters required to ascertain the column density of dust or its properties are interdependent and need to be assumed. One novel method that sidesteps many complications to determining the properties of dust and test dust models is to study it using two different radiative processes simultaneously. You will test dust models by observing dust scattered light images from the Dragonfly Telephoto Array (, and thermal dust emission images from the Herschel Space Observatory. You will learn advanced image processing techniques, including how to remove stars from your images to enable analysis of the diffuse dust.
    Supervisor: Dr. Jielai Zhang

  • Deeper, Wider, Faster: Discovering the fastest bursts in the Universe
    The Deeper, Wider, Faster (DWF) program is the first program able to detect and study the fastest bursts in the Universe (on millisecond-to-hours timescales), such as fast radio bursts, supernova shock breakouts, kilonovae, all types of gamma-ray bursts, flare stars, and many others. DWF coordinates over 50 major observatories on every continent and in space (gamma-ray through radio), including particle and gravitational wave detectors, with a number of these multi-messenger facilities coordinated to observe the target fields simultaneously. DWF performs real-time supercomputer data processing and transient identification within minutes of the light hitting the telescopes. Fast identification and localisation enable rapid-response spectroscopic and imaging follow up before the events fade using 10m-class telescopes like Keck in Hawaii, Gemini-South and the VLT in Chile, SALT in South Africa, as well as Parkes, ASKAP, Molonglo, and ATCA radio telescopes and 4m AAT optical telescope in Australia and the NASA Swift and Chinese HXMT space telescopes. Finally, our network of over thirty 1-10m telescopes worldwide provide follow-up imaging and spectroscopy at later times. Depending on the interests and experience of the student, the project will involve (1) cross-matching multi-wavelength (radio, optical, UV, x-ray, and gamma-ray) data to discover new transients, (2) creating a system to coordinate and schedule observatories for DWF runs, and (3) enhancing and accelerating transient discovery by progressing data visualisation and data sonification techniques. Participation in DWF observing runs is encouraged and, in some cases, will help test the results of the student project.
    Supervisor: Dr. Jielai Zhang and A/Prof. Jeff Cooke