The postholder will contribute to the EU Horizon Europe HARMONICA project by developing advanced human motion prediction, self-learning algorithms for virtual–real robotic systems to support the safe handling of hazardous elements in End-of-Life (EoL) products. Based at Queen’s University Belfast and working in close collaboration with other HARMONICA consortium partners, the role will focus on integrating real-world robotic inspection with digital twin environments.

About the person

The successful candidate must have, and your application should clearly demonstrate that you meet the following essential criteria:

• Hold or be about to obtain* a PhD *) in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related discipline *must be obtained within 3 months of closing date of post
• Significant, relevant research experience.
• Demonstrated expertise in at least one relevant area such as reinforcement learning, robot learning, autonomous systems, or intelligent control ·
• Experience preparing high-quality visual materials, including technical figures, demonstration videos, and presentation slides ·
• Experience presenting research findings at international conferences, workshops, or industry-facing events.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information on our website.

This post is available until 31^st May 2026. Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.