Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; Swansea University
- ; The University of Manchester
- ; University of Exeter
- ; Manchester Metropolitan University
- ; University of Nottingham
- ; University of Southampton
- ; University of Warwick
- ; Brunel University London
- ; City St George’s, University of London
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Newcastle University
- ; University of Birmingham
- ; University of Oxford
- ; University of Plymouth
- ; University of Reading
- AALTO UNIVERSITY
- University of Cambridge
- University of Newcastle
- University of Oxford
- University of Sheffield
- ; Cranfield University
- ; London School of Economics and Political Science
- ; Loughborough University
- ; The University of Edinburgh
- ; University of Bristol
- ; University of Cambridge
- ; University of Copenhagen
- ; University of Essex
- ; University of Stirling
- ; University of Surrey
- ; University of Sussex
- Abertay University
- Durham University
- Imperial College London
- King's College London
- UNIVERSITY OF VIENNA
- 29 more »
- « less
-
Field
-
This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
-
statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
-
(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
-
, the supervision team have obtained data access to indoor environment sensor data at national scale from a leading industrial collaborator. To pair with this big dataset, outdoor environment data at MetOffice can be
-
datasets, therefore, there will be a focus in the implementation of models for large volumes of data. The project will work in an exciting interface of statistics and machine learning and has the potential
-
This is an exciting opportunity to explore the role of complex microbial communities in promoting resilience and maximising yields in large scale algal bioreactors exposed to different environmental
-
, including: Genomic technologies – hands-on experience in long-read sequencing and variant interpretation Bioinformatics – pipeline development, visualisation, and statistical modelling PRS – applying big data
-
health, funded by UKRI. This post will be situated at KCL, working with and across this large disseminated UK-wide partnership spanning 10+ universities and other organisations across the country
-
-impact questions in environmental economics and labour economics. Key responsibilities for this role includes: Data collection, cleaning, and merging from very large-scale microdata sources (e.g., terabyte
-
problems in health data science. Air pollution is composed of several different environmental pollutants, for example particulate matter (PM10 and PM2.5), ozone (O3), nitrogen dioxide (NO2) and sulphur