Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Exeter;
- University of East Anglia
- ;
- The University of Edinburgh
- University of Nottingham
- AALTO UNIVERSITY
- Abertay University
- Imperial College London;
- Loughborough University
- Manchester Metropolitan University
- Newcastle University
- Swansea University
- The University of Manchester;
- Ulster University
- University of Birmingham
- University of Birmingham;
- University of Bristol
- University of East Anglia;
- University of Exeter
- University of Leeds;
- University of Newcastle
- University of Oxford;
- University of Sheffield
- University of Warwick
- 15 more »
- « less
-
Field
-
the Southwest. Geospatial and engineering analyses will identify optimal sites and system configurations, while collaboration with the Law School will assess legal and regulatory frameworks, planning constraints
-
frequency regulation, energy scheduling, and overall smart grid system optimization. Moreover, such complex interconnections between power system dynamics, communication networks, and information
-
thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
-
, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
-
or crinkled. The PhD student will investigate different biomimetic materials and explore how to build membranes with complicated morphologies that will deliver optimal performance in devices. The project will
-
processing techniques that take full advantage of these capabilities, in order to translate them into optimal radar performance. The purpose of the PhD is to lay down theoretical and practical foundations
-
position aims to conduct holistic modelling and analysis of integrated energy systems to reach optimal system performance while incorporating various sustainable energy infrastructures. Potential research
-
-efficiency trade-offs, using automated configuration to find Pareto-optimal designs under real deployment constraints. 2) Build the distributed learning loop. Develop the learning and update mechanisms
-
of the ELITE system will be optimized, and by-products minimized. A range of material enhancements, electrochemical cell modifications, operational strategies will be explored for improved ELITE performance
-
creating virtual replicas of physical homes, the project aims to monitor and optimize energy usage, personalize living environments, and strengthen security measures. This work requires a comprehensive