Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- ; Swansea University
- ; The University of Edinburgh
- ; City St George’s, University of London
- ; The University of Manchester
- ; University of Birmingham
- Imperial College London
- University of Nottingham
- ; Cranfield University
- ; Loughborough University
- ; University of Nottingham
- ; University of Sheffield
- Abertay University
- The University of Manchester
- University of Strathclyde
- 6 more »
- « less
-
Field
-
Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
-
platform. Training the development digital-twin using real-time data from hardware available Electrical power level studies with developed digital twin to identify visible solutions for distribution electric
-
for distribution electric propulsion. Who we are looking for We are looking for enthusiastic, self-motivated applicants with first-class degree in Electrical Engineering, Aerospace Engineering or Computer
-
: The occurrence and distribution of species within and around solar parks, identifying key “winners and losers” in terms of biodiversity. How species interactions, including plant-pollinator networks
-
, particularly in computer networks, operating systems, computer architecture and distributed systems Excellent programming, system building and measurement skills are required Be familiar with, and ideally worked
-
challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
-
and social acceptance. This research will develop an efficient variable renewable energy (wind and solar) input system architecture to produce, store, and distribute variable power output (electrical
-
refine simulation tools and machine learning solutions to advance stroke treatment. This involves improving existing computational models that simulate cerebral blood flow, oxygen distribution, and brain
-
memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital
-
-shot/Few-shot Learning and Distributed/Decentralized Federated Learning not only provide approaches to combine intelligence but also ensure computational tractability of exponentially growing and