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Real-time control of high-power emissions in miniaturised ultrafast lasers (micro-combs) via machine-learning

   School of Science

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  Dr Juan Sebastian Totero-Gongora, Prof Alessia Pasquazi  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Miniaturised frequency combs (micro-combs) are advanced lasers emitting ultra-precise pulses of light [1]–[3]. They are ideal candidates to provide the fast-beating “optical heart” required by transformative technologies such as portable atomic clocks, highly-sensitive hazardous chemical detectors, medical wearable, and computer chips operating at photonics speed [4]. Despite recent technological breakthroughs, micro-combs remain hard to control at the high emission powers required by real-life applications, such as optical atomic clocks. This is because existing stabilisation techniques are poorly suited to control highly nonlinear states, limiting our access to the extensive range of potential emission regimes.

This theoretical/experimental PhD project aims to overcome this conceptual gap by developing an advanced approach to characterise a real-life micro-comb laser using advanced data-driven techniques, with the final aim to reconstruct an effective machine-learning model of the experimental system suitable for real-time control [5], [6]. During the project, the PhD will be directly involved in the development and testing of machine learning control models in numerical simulations and real-life experimental setups.

At the end of the PhD, the candidate will have developed a thorough expertise in applied machine learning, experimental ultrafast photonics, and micro-comb science. To this end, the PhD project has been allocated a generous travel and training budget available for technical and professional development. We particularly welcome applications from under-represented groups, including, but not limited to BAME, disabled, neurodiverse, and female candidates.

Research Group and environment

The PhD research project will be undertaken under the supervision of Dr Juan S. Totero Gongora, Senior Lecturer in Experimental Physics and EPSRC Quantum Technology Fellow. The research group is funded by a recently awarded £1M Quantum Technology Career Development Fellowship ( 

The research group is part of the Emergent Photonics Research Centre ( led by Prof. Marco Peccianti and Prof. Alessia Pasquazi. The Centre has been established in 2022 thanks to significant investment from Loughborough University in nonlinear photonics and quantum technologies. It comprises several research groups focused on micro-comb lasers (Prof. Pasquazi), terahertz imaging and communications (Prof. Peccianti), and machine learning control of high-power lasers and neuromorphic photonics (Dr. Totero Gongora). 


Primary Supervisor: Dr Juan Sebastian Totero Gongora

Email: [Email Address Removed]

Secondary Supervisor: Prof. Alessia Pasquazi

Email: [Email Address Removed]

Entry requirements for United Kingdom

Students should have, or expect to achieve, at least a 2:1 in Physics or Engineering. We will also consider atypical scientific/tecnological backgrounds.

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.

Find out more about research degree funding

How to apply

All applications should be made online. Under programme name, select Physics. Please quote the advertised reference number: SCI23-JTG in your application.

To avoid delays in processing your application, please ensure that you submit the minimum supporting documents. See studentship assessment criteria.

Apply now

Funding Notes

UK fee
Fully funded full-time degree per annum
International fee
Fully funded full-time degree per annum
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment.
Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects starting with advert reference ‘SCI23-’ in the School of Science.


[1] Bao, Nature Photonics, 13, 384 (2019).
[2] Pasquazi, Physics Reports, 729, 1, (2018).
[3] Rowley, Nature, 608, 7922, 303, (2022).
[4] Gaeta, Nature Photonics, 13, 3, 158, (2019).
[5] Lusch, Nature Communications, 9, 1, 4950, (2018).
[6] Kutz, Complexity, 2018, 6010634, (2018).

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