Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; The University of Manchester
- ; University of Birmingham
- ; University of Nottingham
- ; University of Southampton
- University of Cambridge
- ; University of Warwick
- ; Swansea University
- ; Newcastle University
- ; University of Oxford
- ; Loughborough University
- ; University of Bristol
- ; University of Exeter
- ; University of Reading
- University of Manchester
- ; City St George’s, University of London
- ; University of Surrey
- ; University of Sussex
- University of Sheffield
- ; Cranfield University
- ; The University of Edinburgh
- ; University of Sheffield
- AALTO UNIVERSITY
- Harper Adams University
- ; Brunel University London
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Aston University
- ; Coventry University Group
- ; King's College London
- ; Lancaster University
- ; University of Cambridge
- ; University of Leeds
- ; University of Strathclyde
- Imperial College London
- UNIVERSITY OF VIENNA
- University of Oxford
- ; Durham University
- ; Edge Hill University
- ; Manchester Metropolitan University
- ; St George's, University of London
- ; The Open University
- ; University of Bradford
- ; University of East Anglia
- ; University of Greenwich
- ; University of Hertfordshire
- ; University of Hull
- ; University of Plymouth
- ; University of Portsmouth
- ; University of Stirling
- Abertay University
- Durham University
- Heriot Watt University
- KINGS COLLEGE LONDON
- THE HONG KONG POLYTECHNIC UNIVERSITY
- UNIVERSITY OF SURREY
- University of East London
- University of Liverpool
- University of Newcastle
- University of Warwick
- 51 more »
- « less
-
Field
-
integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
-
for candidates with a background in meteorology, climatology, physics, engineering and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world
-
information about the application process, please consult our PhD programme webpage or apply directly by clicking the 'Apply' button, above. Before applying, you should carefully review the research carried
-
. In this project, you’ll have the opportunity to be trained and become a proficient user of a range of advanced experimental techniques. For instance, you’ll learn how to use in-situ X-ray Computed
-
study visa before admission. Eligibility Applicants must hold, or expect to hold, at least a UK upper second-class degree (or non-UK equivalent qualification) in Mathematics, Statistics, Physics, Computer
-
Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ’) as the programme of study You will then need to provide the following
-
satellites, with the potential for travel to test instrumentation in ideal locations. Additionally, the simulation work will focus on developing computational models to validate instrumentation and optimising
-
The role The post is part of the Wellcome Discovery Award research programme “Collective Action for Race Equity in Health and Social Care”, which aims to address and dismantle structural factors
-
equivalent in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the
-
according to how well they meet the following criteria: A first class or strong upper second-class undergraduate degree with honours in Engineering, Physics or Materials Science Excellent English written and