Machine learning models for the prediction of pharmaceutical powder properties

Development of new approaches for understanding and optimizing antisolvent crystallization processes

Security of robotic workflows

O&M cost modelling of large component major replacement in next-generation offshore wind turbines with uncertain failure rates

Plasmonic nanostructures for metal-enhanced applications

Investigating novel reagents in organic synthesis

Automated quantitative inspection of nuclear assets and canisters

Uncovering the predominant factors influencing the transient stability margin in power systems with increasing renewable generation using interpretable machine learning

Development of a modular microfluidic platform for customisable in vitro neuroscience models