Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- ; The University of Manchester
- ; Swansea University
- Imperial College London
- University of Cambridge
- University of Nottingham
- ; Newcastle University
- ; University of Cambridge
- ; University of Exeter
- ; University of Leeds
- ; Brunel University London
- ; University of Birmingham
- ; University of Bristol
- ; University of East Anglia
- ; University of Oxford
- ; University of Sheffield
- ; University of Southampton
- ; University of Surrey
- Harper Adams University
- University of Glasgow
- 11 more »
- « less
-
Field
-
components, with enhanced functionalities capable of gathering extra optical information. The proposed project is to design flat metamaterial optics [1,2,3] and utilise their increased functionality to develop
-
for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
-
sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
-
coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
-
Award summary This studentship provides an annual living allowance (stipend) of £21,470, and full tuition fees (Home fee level only). Overview This project will develop uncertainty quantification
-
This doctoral research will focus on the development, optimisation, and coordinated deployment of advanced aerial platforms, specifically electric vertical take-off and landing vehicles (eVTOLs) and
-
the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
-
, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
-
) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
-
needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You