Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- Newcastle University
- University of Nottingham
- University of East Anglia
- Imperial College London;
- University of Exeter
- University of Exeter;
- The University of Manchester
- University of Cambridge
- Loughborough University
- Swansea University
- UCL
- University of Birmingham;
- University of Cambridge;
- University of Warwick
- Bangor University
- Manchester Metropolitan University;
- The University of Edinburgh;
- University of East Anglia;
- University of Sheffield
- University of Surrey
- ;
- AALTO UNIVERSITY
- Edinburgh Napier University;
- Loughborough University;
- Manchester Metropolitan University
- Swansea University;
- The University of Manchester;
- University of Birmingham
- University of Bradford;
- University of Bristol
- University of Leeds
- University of Nottingham;
- University of Oxford;
- University of Plymouth
- University of Warwick;
- Abertay University
- City St George’s, University of London
- European Magnetism Association EMA
- KINGS COLLEGE LONDON
- King's College London
- Liverpool John Moores University
- Newcastle University;
- Nottingham Trent University;
- Oxford Brookes University
- The Open University;
- The University of Edinburgh
- Ulster University
- University of Bristol;
- University of Essex
- University of Hull;
- University of Liverpool
- University of Liverpool;
- University of Oxford
- University of Plymouth;
- University of Reading;
- University of Sheffield;
- University of Surrey;
- University of York;
- 49 more »
- « less
-
Field
-
(CHF), tailored to complex geometries typical of fusion reactor cooling systems. Compile a comprehensive dataset of boiling parameters to support machine learning-based analysis of two-phase flow
-
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
-
sluggish diffusion kinetics of HEAs make them excellent candidates for resisting oxidation and corrosion in high-temperature steam. Guided by thermodynamic modelling and machine learning, we will identify
-
these syndromes occur where and when they do? The student will develop statistical and machine learning models to (i) explain the occurrence of extreme fires and (ii) predict their likelihood under present and
-
approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
-
/PYTHON/R/C programming • Application of Machine Learning Algorithms Additional Information Benefits This scholarship covers the full cost of tuition fees, an annual stipend at UKRI rate (currently
-
and other asset classes Financial econometrics and machine learning. Corporate finance and accounting Corporate governance and shareholder value Corporate finance, networks and insider trading Market
-
implement more effective interventions based on up-to-date predictions. The ideal candidate will have foundational knowledge of machine learning and strong self-motivation. You will be supervised by Dr
-
overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
-
of the workflow. While the majority of the project is computer based, there is a small lab-based component in order to generate cell samples to be able to acquire the NMR data. Once proof of concept has been