Overview
A fully funded PhD studentship is available in the Quantum Technologies Department at the National Physical Laboratory (NPL) in collaboration with the Computer Science Department at Royal Holloway, University of London. The position starts in Fall 2026 and focuses on developing advanced computational techniques that leverage emerging AI and machine learning frameworks to support the realization of large‑scale quantum computing hardware, aiming to achieve practical quantum advantage over conventional systems.
The studentship covers tuition fees for home students and provides a London‑weighted stipend for 3½ years. The successful candidate will be primarily based at NPL in Teddington (Greater London), with regular visits to Royal Holloway, and will work under the joint supervision of Dr. Yannic Rath and Prof. Ivan Rungger.
Responsibilities
* Design and develop computational pipelines that reduce measurement overhead in quantum device characterization by integrating physical knowledge of quantum devices with scalable machine learning approaches.
* Collaborate with superconducting and spin‑qubit research teams to identify and implement low‑noise, scalable quantum gates in experimental systems.
* Support ongoing and forthcoming international collaborations, such as the EPSRC‑ASPIRE UK‑Japan partnership, and help expand research exchange opportunities.
* Contribute to the Quantum Software and Modelling team’s efforts to bridge fundamental research and industrial applications.
Qualifications
* Undergraduate degree in Mathematics, Physics, Computer Science, or a related field.
* Strong foundation in quantum mechanics and machine learning; excellent computer programming skills.
EEO Statement
NPL and DSIT are committed to diversity and equality of opportunity. Applications are encouraged from candidates of all backgrounds, including women, disabled, and black, Asian and minority ethnic individuals. Disabled candidates who meet the minimum criteria will be guaranteed an interview under the Disability Confident Scheme.
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