Federated Bayesian online learning for digital twins with applications to communication systems

This project will investigate the use of distributed agents learning online to predict the behaviour of a physical system though feedback from it. The developed algorithmic framework will serve as an enabler for a Digital Twins (DT) architecture. The focus will be on Bayesian federated learning, as well as of neuromorphic computing. The targeted application of the DT system is the optimization and control of a complex telecommunication system, including 5G and 6G standards.

This will be an interdisciplinary project with the opportunity to work with other top professors at King's while being part of a very collaborative and friendly research group.

The successful candidate should have a background in machine learning, signal processing, and preferably also in information theory.

Application Procedure

To be considered for the position candidates must apply for Engineering PhD via King’s Apply online application system. Details are available at https://www.kcl.ac.uk/study/postgraduate/apply/research-courses

The selection process will involve a pre-selection on documents, if selected this will be followed by an invitation to an interview. If successful at the interview, an offer will be provided in due time.