Sort by
Refine Your Search
-
, and energy efficiency. Advanced Manufacturing: Developing and implementing cutting-edge fabrication techniques (e.g., micro-fabrication, polymer, nanoparticle) to realise the designed metamaterial
-
validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer
-
project will develop novel methods for modelling and controlling large gossamer satellites (LGSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. The candidate will
-
AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
-
of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
-
response have led to targets for reducing overflow frequency, ecological harm, visual impacts, and protecting bathing water. This PhD project has been co-developed with four UK water companies and the
-
on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
-
of complex metagenomic data. You will also become proficient in lifecycle carbon accounting and data-driven decision-making, all mapped to the Researcher Development Framework at Cranfield University. Regular
-
research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
-
to develop enhanced NbS strategies that target micropollutant removal and remain compatible with other ecological and environmental benefits. The aims of this project are therefore to 1) benchmark the long