Published: 17 Mar 2026 390 views
The search for Earth-like planets addresses one of humanity’s deepest questions: are we alone?
Develop a machine-learned model of stellar spectra and instrumental quirks, and use it to discover exoplanets in radial velocity data.
The first exoplanets were detected by the radial velocity method, looking at stellar spectra and measuring the Doppler shift that reveals the tiny gravity of an exoplanet tugging on the star. This remains the cornerstone of exoplanet science today. State-of-the-art instruments, like the Macquarie-built NEID and HPF spectrographs, have the technical capability to detect Earth-like planets – but they are limited by an imperfect knowledge of stellar activity and stellar spectra.
In this project, supervised by instrumentalist Christian Schwab and data specialist Benjamin Pope, we will use machine learning and differentiable programming to understand:
We will:
| Application Deadline | 30 Apr 2026 |
| Value | Fully Funded |
| Country to study | Australia |
| School to study | Macquarie University |
| Type | PhD |
| Course to study | View courses |
| Sponsor | Macquarie University |
| Gender | Men and Women |
The scholarship comprises:
The value of this stipend scholarship is $39,700 per annum (full time, indexed) for three years.
Before submitting your application, submit an expression of interest (EOI) to Benjamin Pope at [email protected].
Your EOI should include the following documents:
For more information, kindly visit Macquarie University scholarship webpage.