PhD Scholarship in Advanced Signal Processing and Data Analytic Techniques for Power System Asset Management University of Queensland, School of Information Technology and Electrical Engineering Australia

PhD Scholarship in Advanced Signal Processing and Data Analytic Techniques for Power System Asset Management


Job no:506989

Area:Faculty Of Engineering, Architecture & Info Tech

Salary (FTE):RTP Scholarship NON-BANDED ($27,596.00 - $27,596.00)

Work type:Full Time - Scholarship

Location: St Lucia, Brisbane

School of Information Technology and Electrical Engineering


Job reference number - 506989


It is an exciting time to get involved with the School of Information Technology and Electrical Engineering, located on UQ’s St Lucia campus.  The School is ramping up its investment in teaching, research and engagement to create an inspiring, diverse and flexible workplace. The direction is backed by a bold, new strategic vision to ensure the School is at the forefront of meaningful research outcomes and pedagogy across its core impact areas of health, data, automation and energy. Boasting strong student enrolments in professionally accredited programs, combined with world-class researchers and facilities, the School is focused on strengthening its position in the global computer science and engineering communities.  By attracting the brightest minds and fostering a truly innovative and collaborative work environment, the School will develop global solutions to contemporary issues and mentor the leaders of tomorrow.


The role

We are seeking one talented PhD candidate to develop advanced signal processing and novel data analytic techniques for power system asset management. With the advancements in electronics technologies, it is relatively easy to collect raw data from condition measurements of power system assets. However, extracting useful information from raw data and subsequently making an informed assessment on asset condition are still challenging. The objectives of this project include:

  1. To investigate the efficient deployment of an optimal set of sensors to provide sufficient visibility of the condition of power system assets.
  2. To apply compressive sensing techniques for an effective data acquisition while preserving the primary characteristics of measurement data without significant information loss. 
  3. To develop novel data analytic techniques for extracting useful information from large datasets and subsequently transforming such information into knowledge regarding the condition of power system asset.
  4. To develop data fusion algorithms to integrate various condition measurement results and all available information and subsequently determining the health status of an asset and predict its remaining useful life.
  5. To deploy the signal acquisition, signal processing, data analytic and information fusion algorithms to field condition monitoring of power system assets.


It is expected that the techniques developed in this project will improve condition assessment of power system assets and provide a means for safeguarding Australian power system networks. The outcomes of the project will also pave a way for Australian utilities to make their assets more suitable for integration into a smart grid environment.


The student should have background knowledge in signal processing, machine learning and power engineering. The successful candidate will have the benefit of top mentorship from academic and industry connections as well as access to UQ’s world-class laboratory and computing facilities.


The person

This scholarship is open to Australian citizens and international applicants. Applicants should possess upper second class honours degree in Electrical Engineering or in Computer Science from an Australian University or a Master’s Degree with a high GPA from a reputed overseas University. The candidates should also have good general research skills, a strong methodological background, excellent analytical skills, very good writing ability and the capacity to work with industry professionals.



This is funded PhD scholarship at the Australian Government’s RTP rate of $27,596 per year (2019), tax-free for three years with the possibility of two 6-month extensions in approved circumstances. Some top-up scholarship will be considered based on the selected student’s credentials.


For further information on scholarships please refer to:


Starting date 

This PhD position will start in RQ2 2019.



To discuss this role please contact Dr Hui Ma via Email


To submit an application for this role, please use the Apply button below. It is mandatory that all applicants MUST supply the following documents: Cover letter, your detailed resume and complete academic records (including GPA scores/grades, and grading scale details).


For information on completing the application process click here.

Advertised: 15 Feb 2019 

Applications close: 17 Mar 2019 (11:55 PM) E. Australia Standard Time

If you apply for this position please say you saw it on Computeroxy


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