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PhD Studentship in Resilient reconfigurable optical networks

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PhD Studentship in Resilient reconfigurable optical networks

PhD Student

7 May 2026

Location

Cambridge

University of Cambridge

Type

Fully-funded 4-year PhD Studentship

Salary

Fully funded for eligible UK students: tuition fees, maintenance, UKRI stipend + £5,000 top-up

Required Qualifications

Good 2:1 honours degree
Engineering or related
Computer science
Mathematics
Statistics
Physics

Research Areas

Resilient reconfigurable optical networks
Probabilistic machine learning
Network resilience
Transceiver sensing data
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PhD Studentship in Resilient reconfigurable optical networks

PhD Studentship in Resilient reconfigurable optical networks

Applications are invited for a fully funded 4-year PhD studentship at the University of Cambridge to conduct research into resilient, reconfigurable optical networks, in collaboration with BT under the Industrial Doctoral Landscape Award (IDLA) scheme.

Network resilience is the ability of a system to prevent, withstand, and recover from failures. As optical networks become increasingly reconfigurable, the need for human intervention and site visits is reduced, offering the potential for enhanced resilience. However, reconfigurability introduces additional complexity and trade-offs. Understanding the interplay between resilience and reconfigurability therefore requires a probabilistic framework capable of capturing uncertainty and its impact on network performance.

All communication networks operate under varying degrees of uncertainty, ranging from traffic fluctuations to uncertainties in physical layer parameters. In optical networks, many parameters are not directly measurable and are instead specified using conservative, worst-case assumptions. A paradigm shift is now emerging, driven by the availability of real-time sensing data from advanced transceivers and the application of probabilistic machine learning techniques. These approaches enable improved estimation of network states: combining prior knowledge of uncertainty (a priori) with measurement-driven updates (a posteriori) to produce more accurate predictions of failures and overall network availability.

This project will address key research questions, including:

  • To what extent can sensing data from intelligent transceivers and network reconfigurability improve resilience?
  • How can probabilistic machine learning be integrated with transceiver data and network metrics to estimate failure probabilities effectively?
  • How can we characterise the Pareto front that defines the trade-off between cost, complexity, and resilience?
  • What changes are required in network design and operation to improve availability, for example from 99.999% ("five nines") to 99.9999% ("six nines")?

The successful candidate will be based in the Department of Engineering and will have access to the Fibre Optic Communication Systems Laboratory. This includes state-of-the-art experimental infrastructure, such as advanced transceivers, a 1200 km optical line system, a multichannel 120 GSa/s arbitrary waveform generator, and a multichannel 256 GSa/s digital oscilloscope for signal detection.

The student will work closely with researchers at BT, benefiting from regular interaction, industry insight, and feedback from practitioners. The project also offers opportunities for broader engagement with partners across industry and academia.

Applicants should have, or expect to obtain, at least a good 2:1 honours degree (or equivalent) in engineering or a related discipline, such as computer science, mathematics, statistics, or physics. For informal enquiries, please contact Prof. Seb Savory (sjs1001@cam.ac.uk).

EPSRC IDLA studentships provide full funding (tuition fees and maintenance) for eligible UK students, including a tax-free stipend at the standard UKRI rate plus a £5,000 annual top-up. The studentship is funded for four years.

To apply for this studentship, please send your two-page CV to Prof Seb Savory sjs1001@cam.ac.uk to arrive no later than 7th May 2026. Applications may close early if the position is filled before this date.

Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately for admission through the University's Postgraduate Admissions application portal; this can be done before or after applying for this funding opportunity. The applicant portal can be accessed via: www.postgraduate.study.cam.ac.uk/courses/directory/egegpdpeg.

The final deadline for PhD applications is 14 May 2026, although it is advisable to apply earlier than this. Please note there is a £20 application fee. Early applications are strongly encouraged as an offer may be made before the stated deadline.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

Key information

Department/location

Department of Engineering

Salary

Reference

NM49447

Category

Studentships

Date published

16 April 2026

Closing date

7 May 2026

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Frequently Asked Questions

🎓What are the eligibility requirements for this PhD studentship?

Applicants must have, or expect to obtain, at least a good 2:1 honours degree (or equivalent) in engineering or a related discipline such as computer science, mathematics, statistics, or physics. Funding is for eligible UK students under EPSRC IDLA. For more on research jobs, visit research jobs. International applicants may need to secure separate funding.

📝How do I apply for this PhD studentship at University of Cambridge?

Send your two-page CV to Prof. Seb Savory at sjs1001@cam.ac.uk by 7 May 2026. Separately apply for PhD admission via the University Postgraduate Admissions portal (£20 fee). Early applications encouraged. See university jobs for tips.

💰What funding and stipend does this PhD offer?

Fully funded for eligible UK students: covers tuition fees and maintenance, plus a tax-free UKRI-rate stipend with £5,000 annual top-up. Funded for 4 years via EPSRC IDLA. Explore scholarships for additional options.

🔬What is the research focus of this optical networks PhD?

The project investigates resilient reconfigurable optical networks, using probabilistic machine learning with transceiver sensing data to enhance network resilience, estimate failures, and optimize trade-offs in cost, complexity, and availability (e.g., five to six nines). Collaboration with BT. Related advice in postdoctoral research success.

🛠️What facilities and opportunities are provided?

Access to the Fibre Optic Communication Systems Laboratory with advanced infrastructure: 1200 km optical line system, 120 GSa/s waveform generator, 256 GSa/s oscilloscope. Close collaboration with BT researchers and industry/academia partners. Based in Department of Engineeringresearch jobs for similar roles.

When is the closing date and any notes on timeline?

CV deadline: 7 May 2026 (may close early). PhD admission final deadline: 14 May 2026. Offers conditional on admission. Apply early. University promotes equality, diversity, and inclusion.
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