Research Associate in Edge AI

Applications are invited for a position as Research Associate in Edge AI for 6G Wireless Networks and at King’s College London. The position is full-time and fixed term for 30 months (2.5 years).The post is due to start in the first quarter of 2023.  

The role will be part of a 6 million euros Horizon Europe project on “AI-powered Evolution Towards Open and Secure Edge Architectures” (VERGE). This is a joint project with academic partners, including UPC, CTTC, the university of Oulu, BSC-CNS, and industrial partners, including Ericsson, Samsung UK, Intel, Turkcell, Nearby Computing, Thales, Hiro, Arcelik, and Holo-light.

You will be a conscientious, innovative scientist who has successfully completed a PhD (or equivalent) in Telecoms, computer science and engineering including electrical/electronic engineering or similar. Experience in designing machine learning algorithms for edge-enabled wireless networks is preferred.

At King’s, you will join a research-leading and multi-disciplinary team led by Dr Yansha Deng. You will be based in the Centre for Telecommunications Research group at the Department of Engineering. The successful candidate will also be expected to collaborate with the project partners and members of the research group.

This post will be offered on a fixed term contract for 30 months. This is a full-time  post – 100% full-time equivalent

The role will involve carrying out research in machine learning for 6G wireless edge networks, with the objective of developing task-oriented dynamic computation offloading and distributed intelligence for edge automation via simulations and prototypes. Research will need to be carried out to:  

• Design communication-efficient distributed learning algorithms for 6G wireless edge networks
• Design task-oriented and semantics-aware communications for 6G wireless edge networks
• Design and prototype Open Edge Computing Platform

The successful candidate will have a strong interest in at least one of these, and a keen interest in the other. The successful candidate will be able to develop skills in the exciting and emerging field of machine learning for future wireless edge networks. 

The role may involve irregular hours, with intense periods of activity leading up to deadlines such as publications or deliverable milestones. 

The key challenges on which the applicant will focus can be briefly defined as the following: 

• Work closely with the Principal Investigators (PIs) to ensure that the aims and objectives of the project are achieved in a timely and effective way.
• Write papers for publication in journals and for presentation at conferences, seminars and other research meetings.
• Participate in relevant events within the institution or externally, in order to build contacts to facilitate the exchange of information and advance thinking.
• Support events, conferences and workshops run by the project to develop the project outputs and research agenda.
• Contribute to the development of further research proposals.

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Essential criteria

Education/qualification and training: 

1.       BSc in Telecoms, Computer Science, Electronic Engineering or related area. 

2.       PhD awarded in relevant topics of Telecoms, Computer Science, Electronic Engineering or related area (or near completion). 

Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting the award of their PhDs will be considered. Should the successful candidate be awaiting the award of their PhD, the appointment will be made at Grade 5, spinal point 30 with the title of Research Assistant until confirmation of the award of the PhD has been received. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6, spine point 31 

Experience: 

1.       Ability to demonstrate a record of peer-reviewed journal publications. 

2.       Publications demonstrating his/her experience in multi-agent deep reinforcement learning/ federated learning, etc. 

3.       Ability to use Python and MATLAB. 

Personal characteristics/other requirements: 

1.       Strong appetite for interdisciplinary research. 

2.       Ability to attend regular meetings with project partners. 

3.       Ability to work collaboratively and independently. 

4.       Good interpersonal / team working skills 

Desirable criteria 

1.       Knowledge of edge computing and 5G/6G wireless networks 

2.       Prototyping experience in open-air interface and Soft-defined Radio 

3.       Experience in edge computing