-
Guildford, the project forms a collaboration between AudioLabs, Fraunhofer IIS (Erlangen, Germany) and CVSSP at the University of Surrey. It builds on work by the co-investigators into virtual acoustics
-
on these materials and subsequently build up an understanding of the relationships between the material properties and the solubility and diffusion of gases/vapours. This project will investigate and develop
-
utilise advances in artificial intelligence, mechanistic modelling, and uncertainty quantification to develop a suite of tools for rapid deployment of models across bioenergy industries (e.g. gasification
-
on the mechanical performance of joints subjected to harsh environmental conditions. This project allows multidisciplinary collaboration between the University of Surrey and Culham Centre for Fusion Energy/United
-
. Nevertheless, their potential to other areas, such as sustainability, is underexplored. Thus, this project aims to research and develop sustainable AI foundation models for time series processing applied
-
into explainable models, while IRL aligns AV decisions with human values, adapting driving objectives as per situational demands. This approach uses neuro-symbolic reinforcement learning to develop interpretable AI
-
signatures of host clinical outcome. Objectives: Develop/refine methods to study BTV-specific B cell responses and antibody repertoires in sheep and cattle. Characterise and quantify BTV-specific B cell
-
excipients and final products. Therefore, this project aims to develop selective and sensitive TSC methodologies to address common characterisation and quantification challenges experienced with full and
-
-clinical to clinical studies. The proposed project is part of an ongoing research collaboration between Dr Carina Dunlop (University of Surrey) and Prof. Gianne Derks (University of Leiden, Netherlands) with