This PhD project, based at the University of Southampton within the EPSRC Centre for Doctoral Training in Quantum Technology Engineering, focuses on developing quantum optimal control (QOC) methods for symmetry-based NMR sequences. The research leverages the power of symmetry in selecting NMR interactions and creating correlated spin states, building on established analytical approaches such as average Hamiltonian and Floquet theory. The project aims to achieve a step change in the efficiency and robustness of NMR experiments by integrating Hamiltonian symmetry, periodicity, and quantum optimal control. Symmetry-based sequences are widely used in solid-state NMR, particularly with magic-angle spinning (MAS NMR), to control the average Hamiltonian and selectively recouple spin interactions.

These techniques enable the creation of multi-spin correlated states, parameter filtering, and structural analysis of materials. Recent advances have extended these methods to liquid-state NMR. However, traditional analytical approaches can be limited by experimental imperfections and the complexity of higher-order Hamiltonians. This project will employ full numerical calculations, guided by symmetry and periodicity principles, to develop new QOC symmetry-inspired sequences.

The approach is expected to significantly reduce optimization time and enable the study of more complex spin systems, including nuclei with spin greater than 1/2. The research will also explore pattern recognition in QOC methods, potentially leading to the discovery of new classes of symmetry-based sequences with semi-analytical descriptions.

The project offers substantial training in scientific, technical, and commercial skills, and possible industrial sponsorship is under consideration. Funding is competitive, with UK students eligible for a 4-year UKRI TechExpert tax-free stipend of approximately £31k per year, and studentships at the UKRI base rate available for EU, Horizon Europe, and international students. Overseas students with external funding are encouraged to apply.

The university supports equality, diversity, and inclusivity, and welcomes applicants seeking part-time study. The application deadline is 31 July 2026, with an earlier deadline of 31 March 2026 for international applicants. For further information, contact Professor Marina Carravetta ([email protected]).