Sort by
Refine Your Search
-
Zero are burgeoning areas, so the successful candidate will develop important transferable skills that will be highly-desirable in the future process industries. Number Of Awards 1 Start Date 1st October
-
industrial practice relies heavily on empirical optimisation, leading to inefficiencies in energy use and impurity removal. This PhD project proposes to develop a Coupled Computational Fluid Dynamics-Discrete
-
and optimization but lack frameworks to continuously verify AI safety in operational contexts. This project aims to develop a dynamic validation framework for AI systems using high-fidelity digital
-
of £25,726 plus a research training support grant of £20,000 and 100% fees paid. Overview This PhD project aims to develop a computationally efficient framework for the real-time prediction of river water
-
supply-demand deficits becoming widespread by the 2050s. To effectively plan for water supply resilience, it is essential to robustly model future changes in hydrological systems. This project will develop
-
. There will be scope for both observational and theoretical work, as we develop ever more sophisticated reverberation mapping models that account for general relativistic and radiative transfer effects, and
-
, trustworthy AI for the real-world applications, gaining hands-on experience with the latest AI technologies, contributing to knowledge transfer, and receiving opportunities to develop leadership, and research
-
and the Department for Transport. The aim of this PhD project is to develop a unified approach for risk analysis of cyber-physical transport systems. Essential transportation services are increasingly