Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; University of Warwick
- ; The University of Manchester
- ; University of Nottingham
- University of Nottingham
- ; University of Exeter
- ; University of Leeds
- ; University of Surrey
- ; Cranfield University
- ; University of Birmingham
- ; University of Oxford
- University of Cambridge
- ; Manchester Metropolitan University
- ; Newcastle University
- ; The University of Edinburgh
- ; UWE, Bristol
- ; University of Bristol
- ; University of East Anglia
- ; University of Reading
- ; University of Southampton
- Abertay University
- Imperial College London
- University of Newcastle
- ; Aston University
- ; City St George’s, University of London
- ; Durham University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; King's College London
- ; Loughborough University
- ; Midlands Graduate School Doctoral Training Partnership
- ; Queen Mary University of London
- ; Swansea University
- ; University of Greenwich
- ; University of Strathclyde
- ; University of Sussex
- Harper Adams University
- Liverpool John Moores University
- Newcastle University
- University of Liverpool
- University of Oxford
- University of Sheffield
- 32 more »
- « less
-
Field
-
through the following objectives: Develop a novel approach to investigate the fluid-solid coupling effect on the performance of the CMF; Using machine-learning (deep learning) methods to develop a
-
with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
-
, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will have experience in one or more of these subject
-
., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
-
One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
-
cobalt-free cathodes. The project can involve aspects of materials synthesis, x-ray diffraction and crystallography, scientific software development and machine-learning enhanced analysis depending
-
We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
-
to machine learning and deep neural networks, into the DG finite element solver to reduce computational costs while maintaining the accuracy. The key objective of this work will be to provide step-change
-
Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
-
science, along with proven skills in prototyping software using real-time 3D engines and implementing machine learning models. With 50+ researchers and PhD students, the Centre for Sustainable Cyber Security (CS2