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Fully–funded PhD Studentship – Intelligent Optical Networks enabled by Machine Learning

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Applications are invited for a fully-funded PhD studentship, in the Optical Networks Group, Department of Electronic and Electrical Engineering at University College London (UCL). The studentship is associated with the £6M, 6-year EPSRC Programme Grant TRANSNET (Transforming networks - building an intelligent optical infrastructure), a research programme grant recently awarded to a team of researchers from UCL, in collaboration with Aston and Cambridge Universities and leading industrial partners. The aim of TRANSNET is to create an adaptive intelligent optical network, that is able to dynamically provide data transmission capacity where and when it is needed – a transformative approach for the next-generation digital communications infrastructure. The group at UCL, is a leading research team integrating machine learning techniques into optical transmission systems and network architectures.

See our recent work in this area at https://arxiv.org/abs/1804.04097

The structure of the programme together with the research themes can be found here:
https://www.ucl.ac.uk/transnet-programme/

Studentship

The PhD student will be part of a world-leading team working on the design of future, adaptive optical networks and intelligent transceivers. It is envisaged that these will be enabled by machine learning techniques, digital signal processing, advanced modulation formats and coding; all taking account of nonlinear optical channel properties.

Research will focus on the optical networks underpinning the cloud infrastructure – from long-haul submarine networks to the shorter reach data centre and access networks. Some of the overall goals of the programme are to :
 Develop new approaches to the design of network topologies and architectures, tailored to application requirements: throughput, scalability, latency and resilience.
 Quantify fundamental limit to network-wide throughput, in the adaptive network regime, taking into account optical fibre nonlinearities.
 Develop a family of low-complexity intelligent transceivers capable of operating on different time- and distance-scales: overall delay bounded by propagation delay of fibre.

An ideal student for this programme would be motivated to deliver the next generation of optical network infrastructure using new and emerging technologies for optimisation, artificial intelligence/machine learning and optical network design.

How to Apply

To make informal inquiries, please send a CV, including a list of any publications, with the contact details of at least two referees to Prof Polina Bayvel () who will also be happy to answer any questions about this project.

Students should also complete the UCL online application form for postgraduate admission:
https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/electronic-electrical-engineering-mphil-phd

Please clearly mark your application as : ONG-TRANSNET
Full details can also be found on https://www.ucl.ac.uk/electronic-electrical-engineering/about/vacancies

Funding Notes

The studentship can start at any time and we will continue recruitment on a rolling basis until the position is filled. The generous award, with the potential to be partially-funded by project partners inc MicrosoftAlcatel Submarine Networks, KDDI Japan and others, will cover UK/EU tuition fees and a tax-free maintenance stipend (including London weighting), currently £16,999 per annum (2018/2019) plus an industrial top-up as well as support for equipment and travel.

Related Subjects

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