Position Overview
We are seeking a Postdoctoral Fellow to join the School of Electrical Engineering and Robotics, Faculty of Engineering at Queensland University of Technology (QUT). The Fellow will work on a collaborative project between QUT, other universities and industry partners, focusing on Power Quality Analysis and Modelling using advanced machine learning and data‐driven approaches. The project is part of the ARC Training Centre in Electrifying Australia for a Net‐zero Future.
Key Details
* Term: Fixed‐term, full‐time basis for two (2) years.
* Location: Gardens Point.
* Reference number: 26169.
* Remuneration (LEVA): AUD$96,342 to AUD$130,727 per annum (inclusive of AUD$81,410 to AUD$110,466 salary, 17% superannuation and 17.5% recreation leave loading).
* Remuneration (LEVB): AUD$137,608 to AUD$163,427 per annum (inclusive of AUD$116,280 to AUD$138,097 salary, 17% superannuation and 17.5% recreation leave loading).
Responsibilities
* Collaborate on the Power Quality Analysis and Modelling project with QUT, partner universities and industry.
* Apply and develop machine learning methods such as time‐series modelling, dynamic behaviour prediction, graph neural networks, anomaly detection and physics‐informed neural networks to large‐scale power quality data.
* Analyse voltage and current harmonics from complex, time‐varying distribution networks with grid‐connected inverters.
* Predict system behaviour under different operating conditions and support the design of reliable, stable and high‐performance power systems.
* Prepare technical reports, publish research findings in high‐quality conferences and journals, and communicate results to scientific and industry partners.
* Maintain accurate records and protect intellectual property in accordance with research confidentiality standards.
* Engage and collaborate actively with industry partners and scientific organisations or individuals.
Qualifications
* Completion of a PhD in Electrical or Computer Systems Engineering, or a closely related discipline, with a strong background in machine learning.
* Proficiency in machine learning frameworks such as PyTorch or TensorFlow and strong Python programming skills.
* Experience in power system harmonics and power quality is an advantage.
* Demonstrated written communication skills and a track record of publishing in reputable conferences and journals.
* Commitment to equity, diversity and Indigenous Australian engagement.
* Adherence to ethical research standards, including confidentiality and intellectual property protection.
Benefits
* Competitive remuneration with up to 17% superannuation and 17.5% recreation leave loading.
* Generous parental leave, including 26 weeks primary carer leave.
* Health and wellness support such as Fitness Passport and discounted private health insurance.
* Purchased Leave Scheme (up to eight extra weeks) and Salary Packaging Scheme.
* Professional development opportunities, including leadership programs, workshops and study assistance.
* Support for Indigenous Australian staff through dedicated initiatives and cultural leave.
* Inclusive workplace culture that values ambition, integrity, inclusiveness, innovation and academic freedom.
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