Machine Learning for Multimessenger Astrophysics: Towards a Coordinated Southern Multimessenger Network

About the research project

The Rubin Observatory’s Legacy Survey of Space and Time (LSST) will transform astrophysics by detecting up to 10 million new transients every night. Hidden among these alerts will be rare and transformative events — kilonovae from neutron star mergers, tidal disruption events, and potentially new classes of phenomena, such as the long-sought optical counterparts of Fast Radio Bursts. At the same time, gravitational-wave interferometers (LIGO/Virgo/KAGRA), high-energy satellites including SVOM, and neutrino observatories will generate complementary triggers. The ability to identify, prioritise, and coordinate follow-up of these rare events across the Southern Hemisphere is one of the central challenges of modern astrophysics.

This PhD project will address that challenge by combining machine learning methodologies with the robotic telescopes led by the University of Tasmania (UTAS). On the gravitational-wave side, the candidate will contribute to the revival of Xpipeline, in collaboration with Prof. Patrick Sutton (Cardiff, UK), developing ML tools for improved detection, glitch rejection, and event classification. On the optical side, the student will work with the Fink broker (Dr. Anaïs Möller, Swinburne) to design classifiers capable of filtering and prioritising LSST transients in real time, optimised to capture the rarest astrophysical events.

A key innovation will be the integration of machine learning outputs with robotic telescope scheduling. UTAS operates robotic telescopes in Tasmania (50 cm and 1.3 m), with new facilities under development in Tahiti, providing critical Southern Hemisphere coverage. Together with TAROT and other Australian facilities, these telescopes can be networked to deliver rapid, intelligent responses to multimessenger triggers. By linking ML-driven classifications with scheduling systems, the candidate will directly shape how these facilities react to LSST, GW, and high-energy alerts, ensuring timely identification and characterisation of the most promising events.

Beyond individual discoveries, the project has a strong strategic dimension. By coordinating UTAS telescopes with TAROT, national facilities, and high-energy missions such as SVOM, the candidate will help build a coordinated Southern multimessenger network. This framework will maximise Australian contributions to LSST and multimessenger, while also contributing to space domain awareness (SSA) by strengthening monitoring and rapid-response infrastructures in the Southern Hemisphere.

Astrophysical impact: The project will open new discovery space across the transient universe. At the same time, it will establish the methodological and organisational framework needed for Australia — and UTAS in particular — to play a leading role in multimessenger astrophysics and SSA in the coming decade.

Primary supervisor

Meet Doctor Karelle Siellez

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

• a living allowance stipend funded by University of Tasmania of $34,315 per annum for 3.5 years
• a relocation allowance of up to $2,000
• a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

A tuition fee offset may be offered to eligible international applicants following competitive assessment 

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Other funding opportunities and fees

For further information regarding other scholarships on offer, and the various fees for undertaking a research degree, please visit our Scholarships and fees on research degrees page.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Ensure your eligibility for the scholarship round by referring to our Key Dates.

Additional eligibility criteria specific to this project/scholarship:

• Applications are open to both domestic and international applicants.
• Candidates should hold a strong undergraduate degree with Honours (or equivalent) in physics, astronomy, computer science, or a related discipline.
• A demonstrated background in quantitative methods and data analysis is required.
• Applicants must also meet the University’s minimum entry requirements for Higher Degree by Research, including English language proficiency

Selection criteria

The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

• Strong academic performance in physics, astrophysics, computer science, or a closely related field.
• Proficiency in scientific programming (e.g. Python, C/C++, or similar) and familiarity with machine learning or statistical modelling.
• Demonstrated ability to work with large datasets and apply quantitative methods to research questions.
• Strong written and oral communication skills, with the capacity to present research clearly to both technical and general audiences.
• Capacity to work independently, as well as within an international, collaborative team environment.

Additional desirable selection criteria specific to this project:

• Prior experience in machine learning frameworks
• Knowledge of astrophysics, gravitational waves, or time-domain astronomy, particularly experience with telescope operations or transient surveys.
• Familiarity with high-performance computing or cloud platforms for large-scale data processing.
• Experience working in an interdisciplinary context, linking physics and data science.
• Evidence of engagement in international collaborations or research projects.

Application process

1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
2. Contact Doctor Karelle Siellez to discuss your suitability and the project's requirements; and
3. In your application:
   • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
   • Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
4. Apply prior to 1 October 2026.

Full details of the application process can be found under the ' How to apply ' section of the Research Degrees website.

Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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