Fully Funded PhD Scholarship — Machine Intelligence towards Collaborative Factory Automation
We are inviting applications for a fully funded PhD scholarship on the topic “Machine intelligence towards collaborative factory automation.”
This project aims to pioneer the next generation of intelligent automation systems that can learn, adapt, and collaborate with other machines in modern factories.
The research will focus on developing generalised intelligence and learning techniques that enable automation systems to operate safely and efficiently in dynamic, multi-agent industrial settings.
The successful candidate will join a multidisciplinary research team under the supervision of Dr. Yuqian Lu and Professor Andrea Raith, working on:
- Foundations of generalised and embodied intelligence for industrial machines
- Machine learning and adaptive control for collaborative automation
- Situational awareness in manufacturing
- System integration, experimentation, and validation with real-world automation systems
Candidate Requirements
We are seeking candidates who:
- Hold (or are completing) a Master’s or First-Class Honours degree in Robotics, Mechatronics, Mechanical Engineering, Computer Science, or a related discipline
- Have strong programming and analytical skills (e.g., Python, ROS, control systems, or machine learning frameworks)
- Are highly motivated to pursue research in intelligent automation
- Possess a can-do attitude and passion for producing excellent research outputs
- Demonstrate excellent interpersonal skills to work with industry partners
Scholarship Details
- Duration: 3–3.5 years (full-time)
- Funding: Covers tuition fees + annual stipend (as per University of Auckland PhD scholarship rate) for 36 months
- Start Date: As soon as possible, no later than September 2026
If you are passionate about shaping the future of intelligent, collaborative automation, we encourage you to apply.
Please send your CV, academic transcript, and a short statement of research interest to
📧 Dr. Yuqian Lu (yuqian.lu@auckland.ac.nz)
as soon as possible, but no later than 1 November 2025.
For further information about the project or research environment, please contact Dr. Yuqian Lu directly.
