Research Associate in Edge AI for RF Sensing and ISAC
Research Associate in Edge AI for RF Sensing and ISAC
Description
Research Associate in Edge AI for RF Sensing and ISAC
Job number ENG03874 Faculties Faculty of Engineering Departments Department of Computing Salary or Salary range £49,017 - £57,472 per annum Location/campus South Kensington Campus - On site only Contract type work pattern Full time - Fixed term Posting End Date 13 May 2026
About the role
We are seeking to hire a Research Associate (Post-Doc) to join the Adaptive Emergent Systems Engineering (AESE) group and the EPSRC National Edge Artificial Intelligence Hub. Edge-AI aims to deliver world class fundamental research to protect the quality of AI data/learning running in Edge Computing environments.
Imperial College is consistently in the top 10 world university rankings with the Department of Computing ranked top of the 2021 UK REF assessment. McCann’s Adaptive Emergent Systems Engineering Group (AESE) at Imperial recently won the 2020 President’s Medal for Outstanding Research.
What you would be doing
This position will carry out research into lightweight AI schemes applied to ISAC: Integrated Sensing and Communications (aka JSAC). The research will involve building demonstrations of such systems, but this is driven from the fundamental theoretical knowledge that underpin them.
This position presents a novel opportunity to work alongside Professor McCann and her UK wide Hub team in realizing their full potential and planning for the future. Edge-AI is a close collaboration of academics and researchers from across the UK as well as partners from industry..
What we are looking for
This position is AI focused and it is expected that the candidate will have a strong background in Deep Learning: (e.g., Transformers, RNN/LSTM, CNN, Residual Networks), Loss Functions and Optimisation. As this is applied to ISAC therefore an understanding of waveforms, radio frequency and communications systems is also required. Evidence of lightweight AI schemes will be an advantage.
You will have A PhD (or equivalent) in an area pertinent to the subject area, i.e. in Computer Science, Electrical Engineering and Electronics or Computer Science with relative experience in firstly AI and then RF sensing and ISAC: Integrated Sensing and Communications (aka JSAC). Proven research in AI for ISAC infrastructures is a must.
Demonstrations of the ability to build proofs-of-concept of such systems with a practical Understanding of Modern AI methods including; Deep Learning: Libraries & Frameworks and Statistical Analysis. Please see job description for full list of requirements
*Candidates who have not yet been officially awarded their PhD will be appointed at Research Assistant level. Salary scale: £43,863 - £47,223 per annum.
What we can offer you
This position presents a novel opportunity to work alongside Professor McCann team in realizing their full potential. Directed by Newcastle University, the EPSRC National Edge Artificial Intelligence Hub consists of 15 academic partners and 75 Industrial partners. Here you will have the opportunity to collaborate and deliver world class fundamental research, co-created with stakeholders from other disciplines and regions, working Edge AI Computing environments.
You will also have the opportunity to continue your career at a world-leading institution. Imperial College is currently ranked #2 in the QS world university rankings with the Department of Computing ranked top of the 2021 UK REF assessment. McCann’s Adaptive Emergent Systems Engineering Group (AESE) at Imperial recently won the 2020 President’s Medal for Outstanding Research.
You will receive a sector-leading salary and remuneration package (including 38 days off a year) and a comprehensive early career development support package including 10 training and development days.
Further information
Full-time, Fixed term to start ASAP for 18 months with potential extension.
In addition to completing the online application candidates should attach:
A full CV A 1 page research statement on how your experience meets the above requirements.
If you require any further details on the role, please contact Ashu Choubey: a.choubey@imperial.ac.uk
For queries regarding the application process contact Jamie Perrins: j.perrins@imperial.ac.uk
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