Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; The University of Manchester
- ; Swansea University
- ; University of Birmingham
- University of Cambridge
- University of Sheffield
- ; University of Southampton
- ; University of Warwick
- ; University of Exeter
- ; University of Nottingham
- ; University of Oxford
- ; Newcastle University
- ; University of Bristol
- ; Cranfield University
- ; Loughborough University
- ; University of Leeds
- ; University of Sheffield
- ; University of Surrey
- ; The University of Edinburgh
- ; University of Sussex
- Imperial College London
- ; Brunel University London
- ; Manchester Metropolitan University
- ; University of East Anglia
- ; University of Strathclyde
- Abertay University
- Harper Adams University
- Newcastle University
- University of Oxford
- ; Aston University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; University of Bradford
- ; University of Cambridge
- ; University of Greenwich
- ; University of Plymouth
- ; University of Reading
- AALTO UNIVERSITY
- University of Newcastle
- ; Bangor University
- ; City St George’s, University of London
- ; Coventry University Group
- ; Durham University
- ; Imperial College London
- ; Midlands Graduate School Doctoral Training Partnership
- ; Queen Mary University of London
- ; Royal Northern College of Music
- ; St George's, University of London
- ; University of Portsmouth
- Aston University
- Heriot Watt University
- University of Liverpool
- 43 more »
- « less
-
Field
-
or compromised IoT devices by analysing encrypted traffic patterns, focusing on metadata, flow characteristics, and timing rather than decrypting payloads. The core challenge is creating features and models
-
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
-
shift in the world of hardware design. On the one hand, the increasing complexity of deep-learning models demands computers faster and more powerful than ever before. On the other hand, the numerical
-
. The student through participation in team meetings and training with the team will deploy a numerical model (4SAIL) to study the combined effects of the vegetation-soil system temperature and canopy reflectance
-
advantage of supercomputing resources at facilities based in Swansea, in the United Kingdom, and overseas. The student will perform the first extended, high precision numerical study of such models, computing
-
will also include evaluating and validating existing numerical models, ensuring their reliability in predicting real-world conditions. This project is supported by brand-new laboratory facilities
-
this, there are further sub-objectives during the investigation to achieve this goal: Predict thermal warpage effects on a supersonic intake at different flight times, coupled to a numerical model for the downstream
-
The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
-
research identifies an active and growing research field, with numerous advancements in the past 18 months. A focus on generative AI agents has progressed capabilities towards exploiting zero-day
-
to date by validating numerical models against test data, before undertaking parametric studies to investigate the sensitivity of the key variables that affect the flexural performance of composite steel