Noise reduction and machine learning approaches for advanced electromagnetic spectrum sensors

This industry linked Higher Degree Research project focuses research on the current physical limitation with miniaturising EMS sensor hardware. The successful candidate will be co supervised by Tactira Pty Ltd and will have the opportunity to undertake an internship embedded within the company. There are several open areas of research that would support this field, specifically:

1. Investigation of adapting Machine Learning technique and digital signal processing to minimise or attenuate induction noise in SDRs for small form factor applications.
2. Investigation of novel techniques to decrease the form factors of ultra-wide band conformal and planner array antenna.
3. Investigation of methods to increase the manufacturability of ultra small form factor SDR, Antenna and RF circuitry

Any advancement or breakthroughs in these areas would significantly improve the ability to build nano scale EMS sensors. Ultimately, this would increase their employability on UAV and static low-profile sites which has massive benefits for commercial applications, as well as defence and government. This project offers an excellent opportunity to conduct research with strong applied outcomes and industry impact.

This is a Defence Tailblazer program, and you can find further information at Defence Trailblazer.

Information on how to apply can be found here HDR Application Process

Eligibility:

Domestic PhD or Research Master's candidates only

Scholarship:

$50,000 per annum (4 years for PhD candidates and 2 years for Research Master's candidates)

Successful candidate MUST commence in Term 1, 2026

How to apply:

If interested, must submit a completed expression of interest form and attach copies of academic transcripts to defence.trailblazer@unsw.edu.au.

Please contact defence.trailblazer@unsw.edu.au if you have further questions. 

Application deadline: 31 December 2025