MAITRI Grant (DFAT) PhD Scholarship at Central Queensland University 2026

The purpose of this scholarship is to develop an integrated, intelligent framework for solar farm monitoring and predictive maintenance by combining autonomous drone-based data acquisition, Edge-AI processing, and Digital Twin-driven analytics.

Two PhD scholarships are available, with one scholarship allocated to each of the following projects:

1. Digital Twin-Driven Predictive Analytics for Fault Forecasting and Maintenance Scheduling of Solar Farms 
2. Edge-AI Enabled Autonomous Drone Systems for Real-Time Fault Detection in Solar Energy Infrastructure

Table of Content

• Summary
• Benefits
• Requirements
• Application Documents
• Application Deadline
• How To Apply

Summary

• Application DeadlineMay 15, 2026
• Study LevelPhD
• SponsorCentral Queensland University (CQUniversity)
• School to studyCentral Queensland University (CQUniversity)
• Eligible CountryAll Countries

Benefits

• Stipend total $AU118,500 ($AU38,000 in Year 1, $AU39,500 in Year 2, and $AU41,000 in Year 3
• Plus Project Support Funding of $AU6,500 for travel support

Requirements

• A Master’s degree or Honours degree (4 years) in Electrical Engineering, Computer Science, Mechatronics, Robotics, AI, Data Science, or related disciplines.
• Strong knowledge of renewable energy systems, embedded systems, AI/ML, or cyber-physical systems (e.g. Edge-AI, Digital Twins).
• Demonstrated interest or experience in either:
  • hardware–software integration (e.g., drones, sensors, GPUs/FPGAs) or
  • data-driven modelling and predictive analytics.
• Enthusiastic, self-motivated, and capable of conducting independent research and development.
• Ability to work in multidisciplinary and international collaborative environments, with strong communication skills.
• Willingness to be based in Rockhampton QLD (Project 1) or Melbourne VIC (Project 2) and undertake research visits to partner institutions in India.
• A valid Working with Children Check (or ability to obtain prior to or upon commencement).
• English language proficiency with a minimum score of IELTS 6.5 (with no band less than 6.0) or an equivalent PTE Academic score of 62.

Desired Skills:

• Experience with drone systems, IoT sensors, or real-time data acquisition.
• Knowledge of machine learning, deep learning, or large-scale data analytics.
• Programming experience (e.g., Python, MATLAB, or similar).
• Familiarity with Digital Twin technologies, simulation platforms, or power/energy systems.
• Prior research or industry experience relevant to AI, robotics, or renewable energy.
• Interest in publishing in peer-reviewed journals and contributing to open datasets. 

The preferred applicants will need to be admitted to CQUniversity as a PhD student, by lodging a successful application for PhD admission through CQUniversity’s online application portal. 

Application Documents

1. CV
2. Cover letter addressing the selection criteria
3. Academic transcripts
4. 3-year research plan, including motivation, state-of-the-art, research questions or hypotheses and publication plan

Application Deadline

How To Apply

• Submit the supporting documentation to Prof. Jamshid Aghaei [email protected] and Dr Ahsan Morshed [email protected] as soon as possible. Applicants may be invited to meet with the research team to discuss their application.

For more information, kindly visit the CQUniversity Scholarship webpage.