Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- ; University of Birmingham
- University of Newcastle
- University of Nottingham
- ; University of Southampton
- ; Brunel University London
- ; City St George’s, University of London
- ; Swansea University
- ; The University of Manchester
- ; University of Exeter
- ; University of Leeds
- Abertay University
- ; Aston University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Edge Hill University
- ; King's College London
- ; Loughborough University
- ; The University of Edinburgh
- ; University of Oxford
- ; University of Sheffield
- ; University of Sussex
- ; University of Warwick
- Imperial College London
- University of Cambridge
- University of Glasgow
- University of Oxford
- 17 more »
- « less
-
Field
-
Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
-
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
-
. Daily activities include coding, data analysis, simulation modelling, and collaboration with industry partners. Some travel to manufacturing facilities and conferences may be required. This funded PhD
-
exploiting the structure of inputs and doing a multivariate complexity analysis. The goal of this project is to develop more efficient parameterized approximation algorithms and preprocessing algorithms (also
-
Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
-
Project details: Surface features are important in additively manufactured parts. While additive manufacturing technology has made great strides in the realisation of complex shapes, topologies and
-
, and scenario analysis techniques to provide support for strategic decision-making and inform policy. The candidate will identify the existing data gaps in quantifying flood risk and explore best
-
. Recent findings have identified complement activation in tuberous sclerosis complex (TSC)—a rare genetic disorder caused by mutations in TSC1 or TSC2, leading to hyperactivation of the mTOR pathway and a
-
contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
-
for 36 month fixed term at 0.6 FTE (22 hours). Key Accountabilites Organising intervention sessions and data collection, including set up, implementation and analysis of the SleepBoost intervention program