Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- ;
- ; Swansea University
- University of Cambridge
- The University of Manchester
- University of Sheffield
- ; The University of Manchester
- ; University of Birmingham
- ; University of Southampton
- AALTO UNIVERSITY
- ; City St George’s, University of London
- University of Newcastle
- ; University of Exeter
- ; Cranfield University
- ; The University of Edinburgh
- ; University of Nottingham
- ; University of Surrey
- ; University of Warwick
- Newcastle University
- University of Bristol
- University of Cambridge;
- ; Brunel University London
- ; Loughborough University
- ; Newcastle University
- ; University of Bristol
- ; University of Cambridge
- ; University of East Anglia
- ; University of Oxford
- ; University of Sheffield
- Harper Adams University
- Imperial College London
- KINGS COLLEGE LONDON
- UCL
- University of Exeter
- University of Oxford
- University of Warwick
- ; Aston University
- ; Coventry University Group
- ; Imperial College London
- ; Manchester Metropolitan University
- ; St George's, University of London
- ; University of Plymouth
- Abertay University
- Brunel University London
- Coventry University Group;
- King's College London;
- Loughborough University;
- Manchester Metropolitan University
- The University of Edinburgh
- The University of Edinburgh;
- The University of Manchester;
- UNIVERSITY OF VIENNA
- UWE, Bristol
- University College London
- University of Birmingham
- University of Exeter;
- University of Glasgow
- University of Greenwich
- University of Liverpool
- University of London
- University of Nottingham;
- University of Sheffield;
- University of Strathclyde;
- University of Surrey
- University of Sussex
- University of Warwick;
- 57 more »
- « less
-
Field
-
will be required to demonstrate their ability to identify fundamental flow features and model these using suitable CFD methods. Experience in Fortran/C/C++/Python/Matlab is an advantage but not essential
-
the optimization-based methods (doi.org/10.1016/j.apenergy.2020.116152 ), 3- Weakness of the model-predictive-control (MPC) against HESS’s parameters uncertainties, noises, and disturbances (doi.org/10.2514/6.2022
-
processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
-
production-grade system that integrates Vision Transformers for visual deepfakes, advanced Natural Language Processing (NLP) models for phishing detection, and a dedicated Explainable AI (XAI) layer
-
approaches to interpreting these large datasets, as well as computational models that capture low-dimensional structure that reflects the architecture of the neocortex. By working with researchers developing
-
vehicles, data centers, etc.). These devices are mostly power electronic interfaced introducing new types of dynamic phenomena and the need for more detailed models, increasing complexity. In addition
-
reduction (MAR) algorithms, AI-based segmentation, and automated 3D anatomical modelling, promise clearer, more reliable imaging. Integrated effectively into clinical workflows, these advances have the
-
health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
-
treatments. COMSOL finite element modelling software will be used to optimise and tailor the application of electrochemical gradients at engineering surfaces, representative of pond furniture. This allows
-
an important role in the efficient integration and management of solar energy in modern power systems. The studentship project aims to develop a novel PV forecasting model based on physics-informed neural