TUO
Noise reduction and machine learning approaches for advanced electromagnetic spectrum sensors
✓ Fully Funded
⏰ Closing Soon
🎓 Computer Science
🎓 Electrical Engineering
🎓 Machine Learning
🎓 Signal Processing
machine learning
Defence Trailblazer
RF circuits
SDR
UAV sensors
antenna design
electromagnetic spectrum
industry-linked
noise reduction
This industry-linked PhD focuses on miniaturized EMS sensor hardware, leveraging machine learning and signal processing to reduce noise, optimize ultra-small form-factor antennas, and improve manufacturability. The project includes potential industry internships and Defence Trailblazer collaboration.
Project Description
The project addresses physical limitations in miniaturizing electromagnetic spectrum (EMS) sensors, aiming to:
Apply machine learning and digital signal processing to minimize induction noise in software-defined radios (SDRs) for compact applications.
Explore novel methods to reduce the form factor of ultra-wideband conformal and planar array antennas.
Investigate techniques to improve manufacturability of ultra-small SDRs, antennas, and RF circuits.
Advances in these areas could enhance nano-scale EMS sensors for UAVs, static low-profile installations, and defence or commercial applications. Alternate related topics may also be considered in consultation with the supervisor.
Entry Requirements
Preference for candidates from Five Eyes countries (Australia, New Zealand, USA, Canada, UK) or domestic PhD/Research Master’s candidates.
Strong background in electrical engineering, computer science, or related areas.
Interest in applied research with industry impact.
Strong background in electrical engineering, computer science, or related areas.
Interest in applied research with industry impact.
How to Apply
Submit a completed expression of interest form and academic transcripts to defence.trailblazer@unsw.edu.au
. For queries, contact the same email.
Further details: HDR Application Process
. For queries, contact the same email.
Further details: HDR Application Process
Eligibility
UK/Home
EU
International
Supervisor Profile
AP
Assoc Prof Benjamin Turnbull
The University of New South Wales (UNSW Sydney), School of Systems and Computing
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