Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- University of Manchester
- ; Swansea University
- ; The University of Manchester
- University of Cambridge
- ; University of Birmingham
- University of Sheffield
- ; University of Southampton
- ; Newcastle University
- ; University of Exeter
- ; University of Surrey
- ; University of Warwick
- ; The University of Edinburgh
- ; University of Nottingham
- ; University of Reading
- ; Cranfield University
- ; University of Oxford
- Harper Adams University
- ; City St George’s, University of London
- ; Loughborough University
- ; University of Bristol
- ; University of Leeds
- ; University of Sheffield
- AALTO UNIVERSITY
- University of Newcastle
- University of Oxford
- ; Brunel University London
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; University of Cambridge
- Imperial College London
- ; King's College London
- ; University of Strathclyde
- ; University of Sussex
- Abertay University
- University of Bristol;
- ; Aston University
- ; Imperial College London
- ; Lancaster University
- ; University of East Anglia
- ; University of Greenwich
- ; University of Hertfordshire
- Heriot Watt University
- The University of Manchester;
- UNIVERSITY OF VIENNA
- ; Coventry University Group
- ; Durham University
- ; Manchester Metropolitan University
- ; Royal Northern College of Music
- ; St George's, University of London
- ; University of Bradford
- ; University of Huddersfield
- ; University of Plymouth
- ; University of Stirling
- Aston University
- Durham University
- KINGS COLLEGE LONDON
- Nature Careers
- Newcastle University
- Nottingham Trent University
- Oxford Brookes University;
- Swansea University;
- UCL;
- UNIVERSITY OF MELBOURNE
- University of Cambridge;
- University of Glasgow
- University of Liverpool
- University of Nottingham;
- University of Warwick;
- 60 more »
- « less
-
Field
-
capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
-
to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
-
motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
-
embanked, drained and reclaimed for agriculture, but now efforts are being made to restore them through a process called managed realignment. A key feature in the design of managed realignment sites is the
-
to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be
-
dioxide (SO2) are commonly measured. Each pollutant is produced and destroyed by different processes, and the levels of the various pollutants are correlated with each other, for example, and increase in
-
-DED process. Finite element analysis (FEA) is widely used to predict the temperature field during the WA-DED process. Traditional FEA models rely heavily on empirical heat source definitions, such as
-
practices for data processing and integration into hydraulic modelling and risk assessment. This project will create a novel methodology for analysing the datasets to achieve meaningful improvements in flood
-
of the mechanisms that lead to defect formation in DED-LB, and improve process control measures to either prevent or mitigate the defects. The additionality of external controls over the laser-matter interactions
-
for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a