PhD in Intelligent Edge Computing for Adaptive Demand Response Management (Smart Grids, Edge AI) Queensland University of Technology in Australia

This PhD opportunity focuses on intelligent edge computing for adaptive demand response management within smart grids, as part of the CSIRO Industry PhD Program. The project aims to advance distributed and edge intelligence for managing distributed energy resources, with the goal of achieving more resilient, secure, private, and responsive smart grid operations. Research will involve developing distributed algorithms and leveraging machine learning and edge AI to optimize energy management at the customer level.

The successful candidate will be admitted to the Queensland University of Technology (QUT) PhD program and will be supervised by a team from QUT, CSIRO Data61, and Energy Queensland. The supervisory team includes Professor Raja Jurdak (QUT), Dr Abdelwahed Khamis (CSIRO Data61), Dr Volkan Dedeoglu (CSIRO Data61), and Kieren Astin-Walmsley (Energy Queensland). The primary research location is QUT's Gardens Point Campus in Brisbane, with industry engagement at Energy Queensland and additional collaboration with CSIRO Pullenvale.

The scholarship package is valued at approximately $47,000 per annum (tax exempt, 2025 rate) for four years, with an additional $13,000 per annum for project expenses and development. The program includes a 60-day industry engagement component and structured professional development and training to enhance applied research skills.

Eligibility is limited to Australian citizens, permanent residents, or New Zealand citizens. Applicants should have experience in programming (C, Python, or similar), and knowledge of machine learning or distributed systems is desirable. Candidates must be prepared to complete onboarding at Energy Queensland, including confidentiality agreements and other requirements.

To apply, contact Professor Raja Jurdak. The position remains open until filled. For more information, visit the project page or reach out to the supervisors via the provided email addresses.