Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- University of Nottingham
- ; University of Exeter
- ; The University of Manchester
- University of Sheffield
- ; Swansea University
- ; University of Birmingham
- ; City St George’s, University of London
- ; Cranfield University
- ; University of Bristol
- ; University of Southampton
- Imperial College London
- University of Newcastle
- ; Aston University
- ; Brunel University London
- ; Loughborough University
- ; The University of Edinburgh
- ; University of Nottingham
- ; University of Sheffield
- ; University of Surrey
- ; University of Warwick
- Harper Adams University
- Newcastle University
- The University of Manchester
- UNIVERSITY OF VIENNA
- University of Glasgow
- University of London
- 18 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
-
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
-
sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
-
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
-
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
-
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
-
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