Symmetry-restricted quantum parameterised circuit generative models

About the Project

Supervisory team: Dr Srinandan Dasmahapatra

Recognising patterns in data to simulate their distributions is a machine learning task that can be enhanced by generating measurement samples from quantum states that are suitably prepared by parameterised quantum circuits. By exploiting symmetry properties, the project will build efficient quantum generative models that have a wide range of applications.

The intersection between the fields of machine learning and quantum computing is an exciting arena for the development of novel algorithms. Measurements on quantum states reveal encoded correlations that go beyond what classical random variables can directly represent. This property makes them a promising component in generative models for learning probability distributions with sample efficiency not achievable using classical methods. The target quantum states are created by quantum circuits with parameterised gates, and the parameters are set using machine learning methods on a classical computer, making it a hybrid quantum-classical approach.

This project will make use of symmetries to constrain the search space of parameters and the representations of states that they generate, in order to guard against training bottlenecks Applications of these methods lie in estimating average values of quantities that characterise a wide range of problems, from chemistry to combinatorial optimisation. While breakthroughs in this research direction is anticipated in all these areas and more, the focus of this project will, however, be restricted to generative machine learning. You'll be part of a vibrant research group where reading groups and discussion forums provide additional sources of analytical thinking, problem-solving and presentation skills.

Entry requirements:

You must have a UK 2:1 honours degree, or its international equivalent.

Fees and funding:

Full scholarships include tuition fees, a tax-free stipend at the UKRI rate for up to 3.5 years (totalling £20,780 for 2025/26, rising annually). UK, EU and Horizon Europe students are eligible for scholarships. Chinese Scholarship Council funded students are eligible for fee waivers. Funding for other international applicants is very limited and highly competitive. Overseas students who have secured or are seeking external funding are welcome to apply.

How to apply:

Apply now

You need to:

• choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Computer Science (7089)
• add name of the supervisor in section 2 of the application

Applications should include:

• research proposal
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)

The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break.

The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.