Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- University of Nottingham
- ; Swansea University
- University of Cambridge
- ; University of Birmingham
- University of Sheffield
- ; The University of Manchester
- ; University of Southampton
- ; University of Nottingham
- ; University of Surrey
- AALTO UNIVERSITY
- The University of Manchester
- University of Newcastle
- ; City St George’s, University of London
- ; Cranfield University
- ; Newcastle University
- ; The University of Edinburgh
- ; University of Exeter
- ; University of Warwick
- University of Oxford
- ; Loughborough University
- ; University of Oxford
- Imperial College London
- Newcastle University
- University of Bristol
- University of Exeter
- ; Brunel University London
- ; University of Bristol
- ; University of Cambridge
- ; University of East Anglia
- ; University of Sheffield
- ; University of Strathclyde
- Harper Adams University
- KINGS COLLEGE LONDON
- The University of Manchester;
- UCL
- University of Glasgow
- University of Warwick
- ; Aston University
- ; Coventry University Group
- ; Durham University
- ; Imperial College London
- ; Manchester Metropolitan University
- ; St George's, University of London
- ; University of Greenwich
- ; University of Plymouth
- ; University of Reading
- Abertay University
- Coventry University Group;
- King's College London;
- Loughborough University
- Manchester Metropolitan University
- Nature Careers
- The University of Edinburgh
- The University of Edinburgh;
- UNIVERSITY OF VIENNA
- UWE, Bristol
- University of Birmingham
- University of Cambridge;
- University of Greenwich
- University of Liverpool
- University of London
- University of Nottingham;
- University of Sheffield;
- University of Strathclyde;
- University of Surrey
- University of Warwick;
- 58 more »
- « less
-
Field
-
cardiovascular image analysis, but they are limited by their dependence on large, expert-annotated datasets, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where
-
of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
-
targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
-
functional motifs are encoded in HS chains and how they influence their biological activity. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids
-
, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow
-
effective delivery of expertise, equipment, and medical resources in response to complex and large-scale emergencies across the United Kingdom. In its initial phase, the research will examine past and
-
patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
-
sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
-
Water, the student will use the Complex Value Optimisation for Resource Recovery (CVORR) methodology to design a practical decision-support tool for identifying, quantifying, and advancing circular
-
diseases, but is frequently misunderstood, forgotten, and missed. As a toxic proteinopathy that leads to progressive fibrosis, it offers a powerful model for studying common pathways in CKD and represents a