Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- University of Nottingham
- ; University of Nottingham
- ; University of Exeter
- ; University of Warwick
- ; City St George’s, University of London
- ; Swansea University
- ; University of Leeds
- ; Newcastle University
- ; University of Oxford
- ; University of Surrey
- ; The University of Edinburgh
- ; University of Birmingham
- ; University of Bristol
- ; University of Reading
- ; University of Southampton
- Abertay University
- Imperial College London
- University of Cambridge
- ; Aston University
- ; Brunel University London
- ; Cranfield University
- ; Durham University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Loughborough University
- ; Queen Mary University of London
- ; UCL
- ; UWE, Bristol
- ; University of East Anglia
- ; University of Greenwich
- ; University of Kent
- ; University of Strathclyde
- ; University of Sussex
- Harper Adams University
- Newcastle University
- University of Liverpool
- University of Newcastle
- University of Sheffield
- 30 more »
- « less
-
Field
-
., 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
-
-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
-
Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
-
techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
-
Master’s degree in a relevant discipline (cognitive neuroscience, neuroscience, computational neuroscience, psychology, cognitive science, machine learning/data science/AI). Start date: 1 October 2025
-
. when do we stop modelling? How do we track / score the quality of the model What is the required level of quality over time How can quality be brought to the required level Can Machine Learning, Large
-
environments such as low light, heat haze, and adverse weather is significantly difficult. These conditions not only degrade video quality but also complicate interpretation by humans and machines, making post
-
Technology. Mr Kumar is the module leader for Military Vehicle Dynamics, part of the Military Vehicle Technology MSc, which he teaches in the UK and overseas. He worked on project from the UK Ministry of
-
/surface reconstruction steps, towards accelerating the exploration of Cu exsolution and CO2 conversion pathways on LCO, (ii) fine-tuning machine-learning interatomic potentials (MLIP), e.g. MACE-MP-0, Open
-
experimentation and validation, and machine learning. References of our current/recent work are here: "Automatic Retrieval-Augmented Generation of 6G Network Specifications for Use Cases," IEEE Communications