302 structures-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" scholarships in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- The University of Manchester
- University of Nottingham
- University of Birmingham
- Newcastle University
- Cranfield University
- Imperial College London
- University of Birmingham;
- University of Cambridge
- University of Sheffield
- University of Warwick
- Loughborough University;
- UNIVERSITY OF VIENNA
- University of Oxford
- ;
- The University of Manchester;
- University of East Anglia
- University of Exeter
- University of Strathclyde
- Manchester Metropolitan University
- Swansea University
- University of Bristol
- University of Oxford;
- King's College London
- Newcastle University;
- University of Leeds
- University of Surrey
- Manchester Metropolitan University;
- Midlands Graduate School Doctoral Training Partnership
- Midlands Graduate School Doctoral Training Partnership;
- Royal College of Art
- The Open University
- UCL
- University College London
- University of Bradford;
- University of Cambridge;
- University of Essex
- University of Essex;
- University of Greenwich
- University of Manchester
- University of Sheffield;
- University of Strathclyde;
- University of Sussex
- University of Sussex;
- jobs.ac.uk
- Abertay University
- Aston University
- Bangor University
- Brunel University London
- Brunel University London;
- Cambridge, University of
- Edge Hill University
- Harper Adams University
- King's College London;
- Lancaster University
- Loughborough University
- Oxford Brookes University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- SOAS University of London;
- UCL;
- UWE, Bristol;
- University of Aberdeen;
- University of Bradford
- University of Dundee;
- University of East Anglia;
- University of Exeter;
- University of Hertfordshire
- University of Leeds;
- University of Nottingham;
- University of Plymouth
- University of Strathclyde (UOS)
- University of Surrey;
- University of Warwick;
- University of Westminster;
- 63 more »
- « less
-
Field
-
Midlands Graduate School Doctoral Training Partnership | Warwick, England | United Kingdom | 2 months ago
(LEO). A key early task will be a structured review of data availability and linkage possibilities to refine research questions and ensure feasibility. The project will employ relevant advanced
-
on existing structures of domination (e.g., capitalism, economic growth, technology, politics). Central to discourses challenging the status quo or incremental change regarding a just transition is the need
-
cooperation. By analysing governance structures, power dynamics, and collective-action challenges, it situates biodiversity outcomes squarely within the political processes that shape global environmental
-
supported by the Enhanced Composite and Structures Centre at Cranfield. About the sponsor We will work in collaboration with Cambridge Nanosystems, which is a world leading high quality, high performance
-
to structural design models to quantify the potential impact on key drivers of offshore wind farm economics. Specifically the impact of advanced wake models on wind farm energy yield forecasts, hence revenue, and
-
of Medicine, which is internationally recognised for its work in cardiovascular science, thrombosis, fibrin clot structure and inflammation. The project will be based in the Leeds Institute of Cardiovascular
-
, and data-intensive processing, with real-world applications across aerospace, energy, and infrastructure. Aim This project will pioneer the first-generation structured light projection robotic system
-
. Current XAI methods are often generic and overlook industrial realities. This project will embed user-centric explanations directly into machine learning workflows using structured, ontology-driven
-
structure, stage-structured demography and density dependence, road-crossing mortality, and climate–hydrology drivers to predict population trajectories and evaluate mitigation scenarios. This PhD will equip
-
temporal structure and missing data affect multimodal learning Identifying fundamental trade-offs between accuracy, efficiency, and robustness. The project emphasises foundational machine learning research