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We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more. Find out more about our benefits (opens in a new window) and join us to become part of something special.

Overview

This post is funded by IAA project at the University of Sheffield, in collaboration with Oxford Quantum Circuits. The project is titled “Quantum-enhanced Anomaly Detection with Graph Neural Networks” and is to be delivered by the quantum discovery of science group led by Prof Oleksandr Kyriienko.

The research will involve designing understanding and developing innovative approaches to graph analysing using quantum-enhanced machine learning. These include strong background both in classical machine learning, physics-informed methods, graph neural networks, and quantum algorithms.

The work will include engagement with the OQC team, assumes strong communication skills, timely delivery, and being a part of a collaborative research network across the UK.

The candidate should have a demonstrated background in theoretical physics and machine learning, and 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 at available quantum hardware and work with experimental colleagues to assess its performance.

• Attend regular meetings of the research group, and prepare reports on your work, including analysis of previous results and outlook for the future studies.

• Prepare deliverables for reporting to OQC and presenting at technical meetings.

• Interact and closely collaborate with colleagues in the group, contributing to the team effort to meet objectives and use laboratory time efficiently.

• Provide supervision to junior researchers including master students and PhD students.

• Help with organising 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 funder and other external scientific meetings, planning well ahead of the deadline.

• Organise time to ensure very good knowledge of the background of the area of research, maintaining up-to-date knowledge of relevant literature.

• Be capable of planning your own research activities in discussion with your supervisor, incorporating issues such as the availability of resources, deadlines, project milestones and overall research aims.

• As a member of staff you will be encouraged to make ethical decisions in your role, embedding the University sustainability strategy into your working activities wherever possible.

• Carry out other duties, commensurate with the grade and remit of the post

Person Specification 

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

Essential criteria

• PhD in physics with a focus on machine learning (assessed at: application/interview)

• Strong expertise in mathematically analysing quantum circuits and/or graph neural network-based workflow (assessed at application/interview)

• Experience in writing manuscripts for peer-reviewed journals and technical documents for reporting (assessed at: application/interview)

• Effective communication skills, both written and verbal, report writing skills, and experience of delivering presentations. (assessed at: application/interview)

• Ability to develop creative approaches to problem solving with an appreciation of longer-term implications. (assessed at: application/interview)

• Ability to work in a team and to collaborate effectively with other researchers (assessed at: application/interview)

• Ability to assess and organise resources, and plan and progress work activities. (assessed at: application/interview)

Desirable criteria

• Understanding main working principles of quantum and classical machine learning for various tasks (assessed at: application/interview)

• Familiarity with mathematical techniques describing state-of-the-art quantum machine learning models (assessed at: application/interview)

Further Information

Grade: 7.7

Salary: £38,249 - £46,735 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

For informal enquiries about this job contact Prof Oleksandr Kyriienko, Chair in Quantum Technologies, on o.kyriienko@sheffield.ac.uk. 

Next steps in the recruitment process

The selection process requires approvals and background checks by founder (DSTL) and needs to be performed prior to starting the post. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process you can contact hicks-hr@sheffield.ac.uk.

Our vision and strategic plan

We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window).

What we offer

• A minimum of 41 days annual leave including bank holiday 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 (for example, Race Equality, LGBT+, Women’s and Parent’s networks).

• Recognition Awards to reward staff who go above and beyond in their role.

• A commitment to your development access to learning and mentoring schemes

• A range of generous family-friendly policies

  • paid time off for parenting and caring emergencies

  • support for those going through the menopause

  • paid time off and support for fertility treatment

  • and more

More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).

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.

We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision (www.sheffield.ac.uk/vision) outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.