Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- The University of Manchester
- Imperial College London;
- Loughborough University
- Newcastle University;
- University of Bristol
- University of East Anglia
- University of Newcastle
- University of Oxford;
- University of Surrey
- University of Warwick
- ;
- ; University of Exeter
- European Magnetism Association EMA
- Harper Adams University
- Newcastle University
- Oxford Brookes University
- UNIVERSITY OF VIENNA
- University of Birmingham
- University of Birmingham;
- University of Cambridge
- University of Cambridge;
- University of Glasgow
- University of Leeds
- 15 more »
- « less
-
Field
-
with symptoms. However, our brain operates differently between sleeping and waking brain states, and an optimal system should take this into account. The aim of this project is to develop brain state
-
-terminal antennas and beamforming operating in FR1 bands and future FR-2, enabling robust terrestrial–satellite integration for safety-critical air mobility services. To develop AI-based algorithms
-
designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
-
. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis
-
samples. All computational methods and algorithms will be implemented as part of the python based MetaboLabPy platform (https://doi.org/10.3390/metabo15010048 , https://github.com/ludwigc/metabolabpy
-
GNSS alone leaves systems vulnerable to interference, spoofing, or outages, particularly in dense urban environments. The development of 6G networks with integrated TN and NTN infrastructures provides
-
Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
-
modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
-
Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
-
interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association