Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- ;
- ; Swansea University
- ; University of Birmingham
- ; The University of Manchester
- University of Cambridge
- University of Sheffield
- ; University of Southampton
- ; University of Surrey
- University of Newcastle
- ; City St George’s, University of London
- ; Cranfield University
- ; Newcastle University
- ; University of Exeter
- ; The University of Edinburgh
- ; University of Nottingham
- AALTO UNIVERSITY
- The University of Manchester
- ; Loughborough University
- ; University of Bristol
- ; University of Oxford
- ; University of Warwick
- Imperial College London
- University of Bristol
- University of Exeter
- ; Brunel University London
- ; University of Cambridge
- ; University of East Anglia
- ; University of Sheffield
- Harper Adams University
- KINGS COLLEGE LONDON
- Newcastle University
- University of Oxford
- ; Aston University
- ; Coventry University Group
- ; Durham University
- ; Imperial College London
- ; Manchester Metropolitan University
- ; St George's, University of London
- ; University of Greenwich
- ; University of Leeds
- ; University of Plymouth
- ; University of Reading
- ; University of Strathclyde
- Abertay University
- Coventry University Group;
- King's College London;
- Loughborough University
- Manchester Metropolitan University
- The University of Edinburgh
- The University of Edinburgh;
- The University of Manchester;
- UCL
- UNIVERSITY OF VIENNA
- University of Birmingham
- University of Cambridge;
- University of Glasgow
- University of Greenwich
- University of Liverpool
- University of London
- University of Nottingham;
- University of Sheffield;
- University of Strathclyde;
- University of Surrey
- University of Warwick
- University of Warwick;
- 57 more »
- « less
-
Field
-
mitigation strategies to prevent performance losses due to these impurities. We will explore both experimental techniques as well as computational models to provide feedback for designing higher efficient
-
verification methodology and corresponding toolchain to detect and mitigate such threats to CPS at the design time making the CPS resilient-by-design. Typically, CPS are modelled as hybrid systems, comprising
-
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
-
of the assembly of these complex microbial communities using ecological theory and mathematical models. The questions we address are: (1) how does the microbial community change during cultivation
-
correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
-
noise models, leading to metrics devoid of assumptions about noise impacts (e.g., cross-talk or non-Markovian noise in gate fidelities). As shown by the supervisory team, non-Markovian noise can be a
-
marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
-
determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new
-
of novel AM materials on corrosion response of key component and develop a model to predict their behaviour. To address the goals set for tackling international climate change, the power sector needs
-
. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids from induced pluripotent stem cells (iPSCs) to create in vitro models for studying