Postdoctoral Research Associate
| Posting date: | 18 May 2026 |
|---|---|
| Salary: | £38,784 to £46,049 per year |
| Hours: | Full time |
| Closing date: | 17 June 2026 |
| Location: | Durham, County Durham, DH1 3LE |
| Company: | Durham University |
| Job type: | Contract |
| Job reference: | 26000580_1779113633 |
Summary
The Role and Department
Durham University Space Research Centre (SPARC)
Durham University has established its new Durham Space Research Centre (SPARC), a £5 million hub of excellence for interdisciplinary space research, training and industrial engagement supported by Durham's Strategic Research Fund (SRF). SPARC addresses cross-disciplinary space-related challenges to promote the responsible and sustainable use of space. The successful candidate will be a part of SPARC, collaborating with SPARC researchers and participating in relevant activities. For more information, visit
The Role
Applications are invited for a Postdoctoral Research Associate (PDRA) to support SPARC activities in robotics and AI research topics.
This post is fixed term for 24 months. Successful applicants will, ideally, be in post by September 2026.
The successful candidate will be managed by Dr Nikos Mavrakis and Prof. Hubert Shum (Computer Science Department) and expected to collaborate with Prof. Atanu Chaudhuri (Business School), as well as other members of SPARC.
After their end of mission operations, satellites are decommissioned either by deorbiting or by moving to a high-altitude orbit. Even in an inactive state, satellites contain valuable materials and components that could be reused as a resource for future missions. To optimise this recycling process, an optimal circular pathway for the parts and sub-parts in the satellites need to be developed, considering the condition of the materials, the costs of processing and the environmental impact. The recent breakthroughs in AI, machine vision and robotics provide the technological foundation for the concept of satellite recycling. Visual inputs enable effective identification of components and their conditions, while multi-sensory data supports the determination of material types, with AI underpinning the overall decision-making process. Handling of the identified components is performed through robotic manipulation planning, executing the recycling process.
The overarching aim of the project is to determine the optimal circular pathway for satellite parts using AI and supply chain modelling and develop the robotic manipulation capabilities for disassembling the identified sub-assemblies or parts.
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