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Ayushi Mandlik

In my PhD, I would like to develop a machine-learning system that can detect FRBs from the filterbank data produced by radio telescopes, in the presence of realistic radio frequency interference, with a higher recall rate and lower false positive rate than existing widely used FRB finding codes. Once completed, this system shall be deployed on major FRB finding telescopes in Australia (Parkes, UTMOST, ASKAP) and tune the performance to maximise FRB discovery in each of the unique environments. Once a large sample of FRBs has been obtained, I would then analyse the properties of the detected sample to learn more about FRB progenitors and support or reject current theories of FRB origins.

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