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SalaryThe Communications and Signal Processing Group at Imperial College has 3 openings in optimisation, machine learning (ML) and artificial intelligence (AI) for communications. The positions are funded by EPSRC via the future communication systems hubs TITAN and All Spectrum Connectivity (https://www.ukri.org/news/6m-boost-for-the-communications-technologies-of-tomorrow/). While based at Imperial College, the post-holders will join a diverse team from across the UK to develop frameworks and algorithms to drive future communication technologies. Our work ranges from ML and signal processing in the physical layer to network level design, optimisation, and orchestration. Three posts are available with the following respective research focus:
- Adaptable and Robust AI for Networks: Future communication systems will exhibit high levels of heterogeneity across space and time. To cope with these requirements, adaptive, data-driven techniques will be employed, which respond in real-time to the state and requirements of the network and users. This research task will develop techniques which ensure performance guarantees, robustness, and tractability despite the data-driven nature of the system.
- AI as a Network Service: Traditional communication systems have been developed to facilitate the exchange of information either directly from person to person, or in a form accessible to humans. With the emergence of artificial intelligence, communication networks are increasingly used to facilitate machine-to-machine communications, where the purpose is no longer to convey information in human-accessible form, but rather to facilitate machine intelligence. This research effort will identify critical characteristics that differentiate communication needs from AI (e.g., federated and reinforcement learning) from those in traditional communications and jointly incorporate these considerations in optimized network designs and operations.
- AI and ML for Physical Layer: Conventionally, many physical layer designs and operation issues are often formulated as optimization problems. AI and ML offer new, promising approaches to tackling such physical layer issues as massive MIMO, rate splitting multiple access (RSMA), reflective intelligent surface (RIS), reconfigurable intelligent edge (RIE) and spectrum sharing. AI and ML can also lead to new cross-layer designs linking the physical to network layers as well as future communication services. By focusing on the physical layer, the main objective of this research aims to develop novel AI and ML techniques to support advanced physical layer techniques and algorithms as well as cross-layer designs and operations.
These 3 positions would be full time, fixed term of 12 months.
- Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £40,694-£43,888 per annum.
Duties and responsibilities
Research duties include:
- To plan and carry out research in accordance with the project aims and timeframes.
- To propose and investigate new techniques, algorithms and architectures for network design, optimization, and orchestration.
- To verify and characterize system performance both analytically and in realistic simulated testbeds.
- To collaborate and cooperate with other research staff both within and outside Imperial College working on related projects funded by the UK EPSRC.
- To act as the representative for Imperial College in meetings, conference calls and conferences.
- To present research at conferences, workshops, open days, and meetings, and publish research results in journals.
- To develop a sound understanding of ethical and health and safety regulations, and the responsibilities of themselves and their colleagues.
- To comply with relevant College policies, including Financial Regulations, Equal Opportunities Policy, Promoting Race Equality Policy, Health and Safety Policy, Information Systems Security Policy and Intellectual Property Rights and Register of Interests Policies.
- To undertake any necessary training and/or development.
- Any other duties commensurate with the grade of the post as directed by line manager / supervisor.
Essential requirements
Essential requirements include:
- Research Associate: Hold a PhD in Electrical Engineering, Computer Science, Mathematics, or a closely related discipline, or equivalent research, industrial or commercial experience
- Research Assistant: Near completion of a PhD (or equivalent) in Electrical Engineering, Computer Science, Mathematics, or a closely related discipline
- Application of machine learning and/or optimization to communication systems
- Implementation and verification of ML algorithms in code
- Knowledge in machine learning and optimization techniques
Documents
- Research Associate in Intelligent Comunications - JD.pdf
