Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- University of Nottingham
- ; The University of Manchester
- ; University of Exeter
- ; Swansea University
- ; University of Birmingham
- University of Sheffield
- ; City St George’s, University of London
- ; Cranfield University
- ; University of Bristol
- Imperial College London
- University of Newcastle
- ; Brunel University London
- ; Loughborough University
- ; The University of Edinburgh
- ; University of Nottingham
- ; University of Sheffield
- ; University of Southampton
- ; University of Surrey
- ; University of Warwick
- Harper Adams University
- Newcastle University
- The University of Manchester;
- University of Glasgow
- University of London
- 16 more »
- « less
-
Field
-
vehicles, data centers, etc.). These devices are mostly power electronic interfaced introducing new types of dynamic phenomena and the need for more detailed models, increasing complexity. In addition
-
Germany, subject to MPIDR terms and conditions. The role is based within the Mortality and Inequalities Research Group at LSHTM with close partnership with the Department of Digital and Computational
-
within fusion reactors, especially plasma-facing materials (PFMs) exposed to intense heat fluxes and energetic particles. Understanding and predicting how these materials degrade under such conditions is
-
sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
-
manufacturing (3D printing) techniques. The purpose of the studentship is to develop a next-generation in vitro model of aged human skin to evaluate the cytocompatibility of materials used in maxillofacial
-
reacting flow conditions. (iii) Identification of the conditions for which hydrodynamic/thermoacoustic instabilities exist. This studentship is part of an EPSRC funded project (EP/Y017951/1 ) and will train
-
Climate change leads to more extreme weather in the UK and triggers public health responses. However, the impacts of extreme weather at the household level has been largely undocumented and may lead
-
a comprehensive, multi-fidelity suite of liquid hydrogen (LH2) pump models to predict and analyze pump performance, stability, and its interaction with the broader fuel system architecture for a
-
and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
-
November 2025 or as soon as possible thereafter. This PhD project aims to explore how emerging datasets could provide value to the UK’s insurance industry through a combination of data analytics, modelling