Sort by
Refine Your Search
-
Employer
- Cranfield University
- ; City St George’s, University of London
- ; Cranfield University
- ; Swansea University
- University of Nottingham
- ;
- ; Brunel University London
- ; The University of Manchester
- ; University of Birmingham
- ; University of Sheffield
- Abertay University
- Harper Adams University
- Newcastle University
- University of Bristol
- University of Exeter
- University of Sheffield
- 6 more »
- « less
-
Field
-
: this provides capability for accurate and fast modelling of urban drainage, handling the full complexity of flow paths on impermeable surfaces, green space, buildings, pipe networks and BGI features
-
Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. The CDT in Net Zero Aviation is the world’s first
-
to analyse complex datasets, extract meaningful insights, and guide the optimisation of drug molecules. Collaborate with internal groups, including the Centre for Additive Manufacturing (CfAM) to design and
-
). PROJECT The net zero and sustainability targets as well as export cost means that there is increased need to rely on new class of alloys with higher recycle content must be developed for both high strength
-
to the complexity of the mathematical models that describe them. The current consensus is that there are three “types” of viscoelastic chaos: modified Newtonian turbulence, elastic turbulence, and elasto-inertial
-
categories for a better capability of managing the uncertainty related to system complexity and data availability to achieve more accurate RUL estimations The student will have the opportunity to work with
-
systems to act as an oversight of the AI. This is costly, complex, and time consuming, nullifying the benefits of using an AI approach. This project’s two aims are (1) Establish the best approach
-
modelling capabilities for the prediction of energy extraction efficiency, especially focusing on improving the understanding and prediction of the complex flow phenomena, including buoyancy effects in AGS
-
the scalability and robustness of AI in complex environments which is a major step towards the digital transformation of the manufacturing industry. Motivation Automation is key to meeting the growing demand
-
-processing crucial. However, video restoration and enhancement are complex due to information loss and the lack of ground truth data. This project addresses these issues innovatively. We propose using prior