PhD scholarship: Advanced rotor sensing and integrated dynamical control


Enrolment status Currently enrolled students
Student type Domestic students
Level of study Higher Degree by Research
Study area Engineering and Computing
HDR funding type Living stipend scholarship
Scholarship value $28,092 per annum (2020 rate), indexed annually
Scholarship duration Three years with the possibility of two 6-month extensions in approved circumstances
Opening date 22 May 2020
Closing date 8 June 2020


This project involved developing and integrating advanced sensors for fluid velocity sensing and rotor force sensing for miniature drones. These sensors will then be used for high-speed feedback and control of drone dynamics. The student will develop control algorithms for optimising flight based on these sensors.


To be eligible, you must meet the entry requirements for a higher degree by research.

Applications are closed.

Before you get started

If this scholarship has rules, download and read them.

How to apply

To be considered for this scholarship, please email the following documents to Associate Professor Pauline Pounds (

  • Cover letter
  • CV
  • Academic transcript/s
  • Portfolio of prior aerial robotics engineering projects

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the Graduate School's website.

Selection criteria

The successful candidate must have all of the following as a minimum:

  1. Demonstrated ability to construct advanced drone systems and flight control units
  2. Demonstrated ability to develop flight-critical electronics devices for drone control systems, including board-level design
  3. Demonstrated ability to write real-time flight-critical firmware
  4. Demonstrated ability to develop SLAM algorithms and integrate them with working flight hardware

The ideal candidate should have the following:

  1. Industry experience in unmanned aerial systems
  2. Advanced mathematical skills in control and modelling
  3. CASA-recognised drone operation certification
  4. Advanced skills in hardware fabrication
  5. Eligibility for Australian security clearance
Applications are closed.


Associate Professor Pauline Pounds
Applications are closed.

Terms and conditions

Read the policy on UQ Research Scholarships.

A domestic part-time student with carer’s responsibilities, a medical condition or a disability, which prevents them from studying full time may be eligible for scholarship consideration, on a case by case basis.

Applications are closed.