Research Fellow : Learning-Based Communications (EPSRC LeanCom)

Employer: UCL
Job location
Job salary
£35,328 - £42,701 per annum inc. London Allowance
Job term
The post is available from October 2019 for 24 months in the in the first instance.
Job closing date

As part of our work in Deep Learning based Wireless Communications, the UCL Electronic and Electrical Engineering, Information and Communication Engineering Group, invites applications for one (1) postdoctoral research position in Transceiver design based on Neural Networks.The scope of this project is to develop new fundamental data-driven transceiver design by representing the transceivers as deep multi-layered Neural Networks specifically tailored to wireless communications.

We are looking for a talented postdoctoral researcher to join our team and help us fulfil the project’s goals, producing quality research.  The work will involve signal processing design for transceivers using neural networks including algorithm development, simulation and testing, and publishing high quality research papers in high-ranked journals.  The successful candidate will work within an established research team led by Dr Christos Masouros.

Main purpose of the job

Undertaking research, design and development in the context of the EPSRC-funded LeanCom Project ( in the design of new transceiver architectures powered by Deep Neural Networks for complex communications systems (including M2M and IoT). This will involve new fundamental data-driven transceiver design by representing the transceivers as deep multi-layered Neural Networks specifically tailored to address challenges arising in modern communications systems and networks along with the application of such new designs to a wide portfolio of communications systems.

Duties and Responsibilities

  • To participate in the design, validation, evaluation and performance analysis of data-driven solutions based on Deep-Learning as described above and according to the work packages of the LeanCom project. The following areas are of special importance in this project:
    • Physical Layer transceiver design based on Neural Networks (NNs), including parameter and loss function tuning, and performance benchmarking,
    • Block-level design of transceivers including a combination of classical transceiver blocks and NN-based blocks,
    • Signal processing based on NNs to accommodate transceiver hardware impairments and low-specification hardware,
    • Performance analysis of wireless communication systems,
    • System-level simulation based on standards compatible parameters to evaluate performance of the above,
    • Testbed-based implementation, validation and evaluation of the above concepts.
  • To lead the drafting and submitting of papers to high quality peer reviewed conferences and high-profile journals.
  • Presenting the research at international conferences and project meetings.
  • To contribute to the preparation and drafting of research bids and proposals.
  • To contribute to the overall activities of the research team and department as required. To contribute to the induction and direction of other research staff and students as requested.
  • The postholder will carry out any other duties as are within the scope, spirit and purpose of the job as requested by the line manager or Head of Department. As duties and responsibilities change, the job description will be reviewed and amended in consultation with the postholder.
  • The postholder will actively follow UCL policies including Equal Opportunities and Race Equality policies.
  • The postholder will maintain an awareness and observation of Fire and Health & Safety Regulations.


Full details and the person specification can be found in the job description.

Interested applicants are encouraged to make Informal enquiries about the post to Dr Christos Masouros

All applications should be submitted via UCL online

recruitment system at the following link:

Job Reference: 1807127

If you have any queries regarding the application process please contact Vicky Coombes at quoting reference 1807127

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