AI for Advanced Manufacturing

Summary

Positioned within Ulster University’s School of Computing, this research theme explores the integration of artificial intelligence with quantum technologies to advance next-generation manufacturing.

Specifically, this project explores the use of artificial intelligence to optimise the design of quantum computing hardware.

Specifically, it will involve the development of advanced optimisation and machine learning techniques for the design of superconducting qubits, one of the leading qubit modalities used in today’s quantum computers.

The optimal design of superconducting qubits is a highly complex, multi-objective optimization problem. It involves searching over materials, geometries and fabrication parameters to balance competing objectives such as coherence time, anharmonicity and scalability.

Recent experimental breakthroughs highlight the potential impact of making the correct design choices. For example, after a decade of only incremental improvement, a threefold increase in the coherence time of transmons was achieved by replacing the base metal niobium with tantalum.

Subsequent experimentally-driven research has investigated why this is the case, providing clues to further opportunities for better design.

AI-driven optimisation offers a promising parallel route forward. Techniques such as Bayesian optimisation have already proven successful in related contexts, such as optimising silicon quantum-dot entangling logic by tuning device parameters to balance gate speed and fidelity.

This project will develop Bayesian optimization and related approaches for the design of superconducting qubits.

Using software such as Qiskit Metal and Ansys, qubit designs will be constructed and simulated, with AI methods optimizing them to explore the trade-offs between multiple design objectives. It is anticipated that the initial focus of the project will be on transmon design, before extending methods to emerging architectures such as unimons.

The PhD will suit a candidate interested in optimisation, machine learning, and quantum technologies.

The researcher will gain expertise in AI for scientific discovery, while collaborating closely with physicists and engineers on real quantum hardware challenges. By advancing automated design strategies, the project aims to make a meaningful contribution to the development of the next generation of quantum computers.

Applying to Multiple Projects: Applications for more than one PhD studentship are welcome, however if you apply for more than one PhD project within Computing, your first application on the system will be deemed your first-choice preference and further applications will be ordered based on the sequential time of submission.

If you are successfully shortlisted, you will be interviewed only on your first-choice application and ranked accordingly. Those ranked highest will be offered a PhD studentship.

In the situation where you are ranked highly and your first-choice project is already allocated to someone who was ranked higher than you, you may be offered your 2nd or 3rd choice project depending on the availability of this project.

The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education.  We particularly welcome female applicants,as they are under represented within the school.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Clearly defined research proposal detailing background, research questions, aims and methodology

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)

This scholarship will cover tuition fees and provide a maintenance allowance of £21,000* (tbc) per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of approximately £900 per annum is also available.

To be eligible for these scholarships, applicants must meet the following criteria:

• Be a UK National, or

• Have settled status, or

• Have pre-settled status, or

• Have indefinite leave to remain or enter, or

• be an Irish National

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.

*Part time PhD scholarships may be available, based on 0.5 of the full time rate, and will require a six year registration period