Overview
This post is funded by the IAA project at the University of Sheffield, in collaboration with Oxford Quantum Circuits. The project, titled "Quantum-enhanced Anomaly Detection with Graph Neural Networks", is to be delivered by the Quantum Discovery of Science group led by Prof Oleksandr Kyriienko.
The research involves designing, understanding and developing innovative graph‑analysis approaches using quantum‑enhanced machine learning. It requires a strong background in classical machine learning, physics‑informed methods, graph neural networks, and quantum algorithms. The role demands engagement with the OQC team, strong communication skills, timely delivery, and collaboration across a UK research network.
The ideal candidate will have a demonstrated background in theoretical physics and machine learning and will have completed or be in the final stages of a PhD in this or a related discipline.
Main Duties and Responsibilities
* Design and analyse hybrid quantum‑classical graph analysis pipelines.
* Perform an in‑depth review of available quantum and classical machine learning protocols.
* Perform efficient simulations of quantum graph processing.
* Test protocols on available quantum hardware and collaborate with experimental colleagues to assess performance.
* Attend regular research group meetings and prepare reports, including analysis of previous results and outlook for future studies.
* Prepare deliverables for reporting to OQC and presenting at technical meetings.
* Interact and collaborate with colleagues in the group, contributing to team objectives and efficient use of laboratory time.
* Provide supervision to junior researchers, including master‑level and PhD students.
* Help organise events and support activities at the Sheffield Quantum Centre.
* Write manuscripts based on your work and the team’s work for research journals.
* Present work at meetings with funders and other external scientific meetings, planning well in advance of deadlines.
* Maintain up‑to‑date knowledge of the background and relevant literature in the area of research.
* Plan and manage your own research activities in discussion with your supervisor, addressing resource availability, deadlines, milestones and overall aims.
* Make ethical decisions in your role and embed the University sustainability strategy wherever possible.
* Carry out other duties commensurate with the grade and remit of the post.
Person Specification
Essential Criteria
* PhD in physics with a focus on machine learning.
* Strong expertise in mathematically analysing quantum circuits and/or graph neural network‑based workflows.
* Experience in writing manuscripts for peer‑reviewed journals and technical reports.
* Effective communication skills, both written and verbal, and experience of delivering presentations.
* Ability to develop creative problem‑solving approaches with appreciation of longer‑term implications.
* Ability to work in a team and collaborate effectively with other researchers.
* Ability to assess and organise resources, and to plan and progress work activities.
Desirable Criteria
* Understanding of main working principles of quantum and classical machine learning for various tasks.
* Familiarity with mathematical techniques describing state‑of‑the‑art quantum machine learning models.
Further Information
Grade: 7.7
Salary: £38,784 – £46,049 per annum
Work arrangement: Full‑time
Duration: 01.06.2026 to 04.12.2026
Line manager: Chair in Quantum Technologies
Direct reports: N/A
Our website: https://www.sheffield.ac.uk/mps
Benefits
* Minimum of 41 days annual leave including bank holidays and closure days (pro‑rata) with the ability to purchase more.
* Flexible working opportunities, including hybrid working for some roles.
* Generous pension scheme.
* A wide range of discounts and rewards on shopping, eating out and travel.
* A variety of staff networks providing opportunities for social interaction, peer support and personal development (e.g., Race Equality, LGBT+, Women’s and Parent’s networks).
* Recognition awards to reward staff who go above and beyond.
* Commitment to your development with access to learning and mentoring schemes.
* A range of generous family‑friendly policies, including paid time off for parenting and caring emergencies, support for those going through menopause, paid time off and support for fertility treatment, and more.
For informal enquiries about this job contact Prof Oleksandr Kyriienko, Chair in Quantum Technologies, on o.kyriienko@sheffield.ac.uk.
We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.
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