Starting date: any time between June – September 2020 Application deadline: 15 March 2020 or until filled
Duration of study: Full Time
Eligibility: UK/EU students ONLY
Applications are invited for a PhD studentship, fully funded by Microsoft Research, to work in the Optical Networks Group (Head - Professor Polina Bayvel), Department of Electronic and Electrical Engineering, UCL) on the next generation of optical communication infrastructure and technologies to underpin the cloud connectivity.
The studentship covers Home/EU tuition fees and an annual stipend of £17,009 (2019- 2020), increasing annually with inflation, together with a generous top-up of £3k per year. Additional support will cover consumables, books, professional memberships and travel to workshops and conferences, including to different Microsoft locations worldwide.
The studentship is funded for 3 years on a full-time basis, with a possibility of a funded 4th year.
Additional information: The student will work closely with researchers on the EPSRC TRANSNET (Transforming optical networks – building an intelligent optical infrastructure) programme grant, collaborating with researchers at Microsoft Research in Cambridge. This position is one of a dedicated of cohort of students who work on this programme under a series of research studentships, fully funded by industry and/or EPSRC. The Optical Networks Group at UCL has graduated a high number of very successful PhD graduates who have won a series of prizes and awards for their research, and are now working in leading academic and industrial research laboratories in the world.
Optical fibre networks underpin the digital communications infrastructure. The next research challenge is to introduce intelligence so that they able to dynamically provide capacity where and when it is needed – transforming next-generation information infrastructure. Cloud network traffic is expected to more than double every two years and new services with high data rate requirements. Research will focus on developing
new approaches for data-centre optical network interconnection. Next-generation networks will need to be adaptive on different time- and length- scales and be tailored to applications requirements on capacity and delay, physical properties of the nonlinear optical transmission channels, and the information from intelligent transceivers on the network state. They will also need to handle much higher capacities – requiring access to much wider fibre bandwidths than have been used to date. This will need the application of new transmitter and amplifier technologies. The
PhD research will combine hands-on experimental work in the areas of high-speed Terabit/s optical fibre transmission systems, machine learning for optical communications and nonlinear optical fibre modelling to predict the performance of next generation of cloud technology. On the experimental research specifically – we are looking for PhD students to help us develop our recirculating optical fibre loop test-bed to support transmission rates above Terabit/s speeds, expand the usable optical fibre bandwidth using new amplifier and transmitter technologies and develop digital transceivers to enable network intelligence using DSP and machine learning.
Eligibility: UK/EU students ONLY
The successful applicants will be part of the Optical Networks Group, Department of Electronic & Electrical Engineering. Applicants (UK/EU only) should be outstanding academically, ideally have 1st class (or a very good 2’1) undergraduate degree or equivalent in physics, communications or electronic & electrical engineering and a clear aptitude and enthusiasm for research. Experience of hands-on experimental work in a research environment is also a significant advantage, with a preference for optical communications/nonlinear optics/high- speed digital comms and machine learning. The research can include machine learning techniques to enable data-driven insights from physical experiments in optical networks. This aspect will require an understanding of data science and machine learning – where some exposure to machine learning libraries, like Tensorflow or similar, is an advantage. For candidates interested in optical network design, understanding of graph theory, discrete mathematics and algorithms is desirable and competence/fluency with scientific computing is essential for all applicants.
Applications should be made using the UCL postgraduate study application form and mark it to the attention of Polina Bayvel, Optical Networks Group.
Closing date: 15 March 2020 – although we will continue to advertise until this studentship has been filled.