CSIRO Postdoctoral Fellowship in ML/AI: Classifying Radio Galaxies in Large Surveys

The Machine Learning and Artificial Intelligence Future Science Platform will bring together a large number of world-leading experts to explore scientific questions using machine learning techniques. The focus of this position is to apply these methods to radio imaging from CSIRO’s Australian Square Kilometre Array Pathfinder (ASKAP) telescope. ASKAP will undertake an all-sky survey called the Evolutionary Map of the Universe (EMU), which will increase the number of known radio galaxies from millions to 10s of millions. The success of EMU relies on machine learning techniques to find patterns and objects in the radio images, and thereby automatically classify radio galaxies and their multiwavelength counterparts. You will work at the interface of astrophysics and machine learning to enable cutting edge astrophysics.

Essential selection criteria include:

• A doctorate (or will shortly satisfy the requirements of a PhD) in a Platform-relevant discipline area, such as computing, astrophysics or physics. Please note: To be eligible for this role you must have no more than 3 years (or part time equivalent) of postdoctoral research experience.
• A sound history of publication in peer reviewed journals and/or authorship of scientific papers, reports, grant applications or patents.
• Solid knowledge of machine learning techniques and proven ability to develop and apply novel machine learning techniques to complex data sets.
• The ability to work effectively as part of a multi-disciplinary, regionally dispersed research team, plus the motivation and discipline to carry out autonomous research.
• Knowledge of Python, Julia, C, C++ or equivalent.