Job Description

Job id: 072285. Salary: \xc2\xa336,532 - \xc2\xa341,299 pro-rata per annum, including London Weighting Allowance.

Posted: 28 July 2023. Closing date: 02 August 2023.

Business unit: Natural, Mathematical & Engineering Sci. Department: Engineering.

Contact details: Toktam Mahmoodi. Toktam.mahmoodi@kcl.ac.uk

Location: Strand Campus. Category: Research.

THIS VACANCY IS OPEN TO INTERNAL APPLICANTS ONLY

Job description

Applications are invited for a part-time position as Research Assistant/Associate in AI for communication Networks, and 6G mobile network design, including Edge AI, distributed AI, digital twining and energy efficiency in mobile and wireless networks. The position is at 20 hours per week part time at King\'s College London, and a fixed term contract until 28th February 2025.

The role will be part of a \xc2\xa312 million strategic investment of the UK government in project REASON. This is a joint project with academic partners, including Uni of Bristol, Strathclyde, and Southampton, and industrial partners, including Ericsson, Nokia, Samsung UK, Thales UK, and BT.

You will be a conscientious, innovative scientist who is conducting your PhD 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 REASON, including Dr Yansha Deng, Dr Vasilis Friderikos, Prof Toktam Mahmoodi, and Prof Osvaldo Simeone. You will be based in the Centre for Telecommunications Research (CTR) 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 until 28th February 2025. One part-time post at 20 hours per week.

Key Responsibilities

The roles will involve carrying out research in machine learning for 6G wireless networking, including 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 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.

Skills, knowledge, and experience

Essential criteria

Education/qualification and training:

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

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

Experience:

3. Ability to demonstrate a record of peer-reviewed publications.

4. Ability to use Python and MATLAB.

Personal characteristics/other requirements:

5. Ability to work collaboratively and independently.

6. Good interpersonal / team working skills

Desirable criteria

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

2. Expertise and track record in mobile edge computing

King\'s College London