Developing Quantum Computing and AI tools for mRNA structure prediction

About the project

About the Project The aim of this PhD project is to develop quantum computing and AI methods for mRNA structure prediction, in collaboration with a large pharmaceutical company contributing 50% of the award. The project will study how mRNA molecules fold into different structures and develop new computational methods to identify relevant and stable candidates more efficiently. The PhD candidate will build quantum computing approaches for smaller structure-prediction problems, using these to generate promising candidate solutions and machine learning tools to improve and filter them. They will also develop fast screening methods based on generative models, so that families of related mRNA designs can be assessed more quickly. For larger and more realistic cases, the project will investigate how established structure prediction methods can be redesigned for early fault-tolerant quantum computers, including quantum accelerators for optimisation. The candidate should therefore be ready both to develop algorithms for future fault-tolerant devices and to conduct tests on real quantum hardware. Across the project, the student will identify the main bottlenecks in speed, accuracy, and hardware requirements, producing an industry-guided benchmark that connects near-term quantum sampling with future quantum algorithms for drug discovery, vaccine design, and RNA therapeutics.

Research areas