Publisher
source

Marian Florescu

Top university

4 months ago

Quantum Reservoir Computing for Photonic and Quantum Materials Modelling University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Jul 31, 2026

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Country

United Kingdom

University

University of Southampton

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Where to contact

Official Email

Keywords

Computer Science
Electrical Engineering
Materials Science
Mathematics
Quantum Mechanics
Optical Physics
Superconductivity
Quantum Computing
Reservoir Engineering
Nanoscience
Electrodynamics
Quantum Materials
High Performance Computing
Multiphysics Simulation
Photonic
Physics
Machine learning

About this position

This PhD project, based at the University of Southampton within the EPSRC Centre for Doctoral Training in Quantum Technology Engineering, focuses on developing Quantum Reservoir Computing (QRC) as a novel theoretical and computational approach for modeling and designing photonic and quantum materials. QRC leverages the intrinsic dynamics of quantum systems—such as coherence, memory, and nonlinearity—to enable efficient learning, prediction, and inverse design, moving beyond traditional data-intensive or brute-force numerical methods. The research will progress through three main stages: first, establishing physically interpretable algorithms for strongly correlated and open quantum systems; second, exploring quantum neuromorphic architectures using computational models of superconducting, photonic, and hybrid reservoirs to identify energy-efficient learning strategies; and third, applying these frameworks to the inverse design of photonic and quantum structures, demonstrating the potential of QRC to accelerate discovery and optimization in a fully computational setting.

The project is hosted at the Optoelectronics Research Centre (ORC), a world-leading photonics institute with over 90 laboratories and approximately 200 researchers. The ORC offers a comprehensive training program in photonics, computational methods, and professional development, preparing students for careers in both academia and industry. Students will have opportunities to develop advanced skills in high-performance computing, numerical simulation, machine learning, and quantum theory, with access to large HPC/GPU clusters. The ORC is committed to fostering an inclusive and collaborative research environment, recognized by its Athena SWAN award for equality, diversity, and inclusion.

The position is open to applicants from all backgrounds, with full consideration for those seeking part-time study. Funding is available on a competitive basis: UK students receive a four-year UKRI TechExpert tax-free stipend of around £31,000 per year (UKRI minimum plus £10,000), while EU, Horizon Europe, and international students are eligible for studentships at the UKRI minimum rate. Overseas students with external funding are also welcome to apply. Entry requirements include at least a UK 2:1 honours degree or international equivalent in a relevant subject.

The application deadline is 31 July 2026, with an earlier deadline of 31 March 2026 for international applicants. For further information, prospective students are encouraged to contact Professor Marian Florescu at [email protected].

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants must hold at least a UK 2:1 honours degree or international equivalent in a relevant subject. Applications should include a CV, two academic references, degree transcripts/certificates to date, and an English language qualification if applicable. International applicants must apply before 31 March 2026. The university encourages applications from all backgrounds and considers part-time study.

How to apply

Apply via the University of Southampton online portal. Select 'Research' as the programme type, academic year 2026/27, and the Faculty of Engineering and Physical Sciences. Search for the PhD Quantum Tech Eng programme and include the supervisor's name in section 2. Submit your CV, two academic references, degree transcripts/certificates, and English language qualification if required.

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