Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; University of Plymouth
- University of Nottingham
- ; Newcastle University
- ; The University of Manchester
- ; University of Birmingham
- ; Imperial College London
- ; Loughborough University
- ; Swansea University
- ; University of Bristol
- ; University of Greenwich
- ; University of Leeds
- ; University of Nottingham
- ; University of Southampton
- ; University of Sussex
- ; University of Warwick
- AALTO UNIVERSITY
- CZECH UNIVERSITY OF LIFE SCIENCES
- Swansea University
- 10 more »
- « less
-
Field
-
based at the Department of Obstetrics and Gynaecology, University of Cambridge. They investigate the mechanisms by which sub-optimal nutrition in early life can affect reproductive ageing, the impact of
-
and traditional aerobic activated sludge processes are hotspots for extremely high N2O emissions. It is generally considered that imbalances in nitrogen cycling pathways, such as nitrification and
-
investment costs and the need for extensive infrastructure. However, substantial emission reductions can be achieved through low-cost, infrastructure-independent measures —namely, optimizing how ships
-
process. Address blind inverse problems by defining a network to learn distortion functions from data, informing the optimization in the learning process. Refine optimization and learning strategies
-
of the most resource-intensive processes in this sector is the cleaning of processing equipment, which accounts for around 30% of a site's water and energy use. Cleaning is typically done using automated Clean
-
optimise a ‘Digital Twin’ of the Tees estuary to ensure that the NBS are deployed at locations optimal for performance and longevity while operating within the constraints placed upon deployment by other
-
successful, the increasing demand for biochar and its by-products in high-value applications necessitates a thorough examination of the existing process and products to optimize efficiency and enhance overall
-
. Finally, a set of recommendations and a toolkit will be developed to support the optimization of professional support services for dentists. This research will take a realist approach to develop a programme
-
(AI) to process vast amounts of real-time data. Traditional AI models follow a central data collection approach, where raw data from multiple vehicles is continuously transmitted to a remote server for
-
sensors to understand their local surroundings at sea and inform optimal action. To ensure safety requires the ability to reliably detect, image and recognise their environment, in terms of surrounding sea