| Location: | London |
|---|---|
| Salary: | £43,909 per annum, including London Weighting Allowance |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 28th July 2026 |
|---|---|
| Closes: | 2nd August 2026 |
| Job Ref: | 153805 |
About us
Recently re-founded, the Department of Engineering is rapidly expanding into a world-class research and teaching department. Research currently focuses on robotics, telecommunications and biomedical engineering, but we are looking to establish new research themes.
We offer both undergraduate and postgraduate teaching, with a distinctive approach, combining both traditional teaching methods with modern, project-based learning, catering for the needs of our students and the industries in which they will work.
As a new department we have invested in new laboratories and maker space at the centre of the Strand campus in the heart of central London.
For more information: https://www.kcl.ac.uk/engineering
About the role
Applications are invited for a position as a Research Assistant in Machine Learning for Wireless Networks at King’s College London.
You will be a conscientious, innovative scientist who has successfully completed a BSc (or equivalent) in computer science, Telecoms, and engineering including electrical/electronic engineering or similar. Experience in federated learning/deep reinforcement learning is preferred.
At King’s, you will join a research-leading and multi-disciplinary team led by Prof. Yansha Deng. You will be based in the Centre for Telecommunications Research group at the Department of Engineering.
The position is full-time until December 31st 2026, with potential for extension. The post is expected to start in Aug. 2026.
Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information.
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