Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- Cranfield University
- ; Swansea University
- ; The University of Edinburgh
- ; The University of Manchester
- ; Cranfield University
- ; Loughborough University
- ; University of Birmingham
- ; University of Nottingham
- University of Nottingham
- ; Austrian Academy of Sciences
- ; University of Bradford
- ; University of Essex
- ; University of Exeter
- ; University of Reading
- ; University of Surrey
- ; University of Warwick
- ; University of York
- 8 more »
- « less
-
Field
-
Project Overview This is an opportunity to conduct fully funded interdisciplinary research under the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex
-
Sustainability Post-COVID-19 Project Supervisors: Professor Rebecca Randell, Dr Joshua Pink Project Description: The COVID-19 pandemic accelerated the drive to home working and acceptance of the distributed
-
team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most
-
, 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
-
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
-
Project Overview This is an opportunity to conduct fully funded interdisciplinary research under the ‘Sustainable Transitions – Leverhulme Doctoral Training Programme’ at the University of Essex
-
optimisation algorithms to dynamically reconfigure the substation/distribution network settings to enhance the system efficiency. The optimisation algorithms will incorporate the uncertainties associated with
-
ultraprecise clock distribution (QT Mission 4: positioning, navigation, and timing; QT Mission 5: network synchronisation) and practical quantum sources for hybrid networks (QT Mission 2: quantum communications
-
the power of AI/ML and software-defined networking (SDN), and distributed learning methodologies, the research will focus on creating self-configuring, self-optimizing, and self-healing mechanisms for real