14163 - Research Associate
The University of Edinburgh
Salary
£41,885 to £49,798 a year
Location
Edinburgh
Contract type
Full time
Job description
- About
Grade UE07: £41,885 to £49,798 per annum
School of Informatics / College of Science and Engineering
Full-Time 35 hours per week
24 months fixed term contract
The Opportunity:
We are seeking a motivated Postdoctoral Research Associate to advance research in Embodied AI and Spatial AI at School of Informatics, The University of Edinburgh. The position is part of a new research programme led by Dr Liang Zhao, developing AI systems that can perceive, understand, reason about, and act within three-dimensional environments.
The successful candidate will have a PhD (or be close to completing one) in artificial intelligence, robotics, computer vision, machine learning, or a closely related field. They will undertake original research connecting spatial perception and understanding with embodied decision-making and action, developing methods that enable intelligent agents to learn from and interact with the physical world.
We welcome candidates whose research interests align with one or more of the following topics:
Spatial intelligence, 3D scene understanding, and spatial reasoning.
Embodied perception, mapping, and navigation.
Multimodal foundation models and vision-language-action models.
World models for prediction, planning, and action.
Learning from interaction, demonstration, and reinforcement.
Generalisation and adaptation across tasks and environments.
Applicants should demonstrate a strong research track record appropriate to their career stage, strong technical skills, and the ability to work both independently and collaboratively. The successful candidate will contribute to shaping the research programme, publish in leading venues, and collaborate with researchers across AI and robotics, with opportunities to support the supervision and mentoring of student research projects.
This post is full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working. The team currently operates a 100%, i.e. 5 days, on-campus working arrangement which has been agreed by the line manager.
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