Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- Newcastle University
- University of Birmingham
- University of Nottingham
- ;
- KINGS COLLEGE LONDON
- Loughborough University
- University of Cambridge
- University of Cambridge;
- University of Exeter
- University of Sheffield
- European Magnetism Association EMA
- Imperial College London;
- King's College London
- Loughborough University;
- The University of Manchester;
- UNIVERSITY OF VIENNA
- University of Birmingham;
- University of East Anglia
- University of Exeter;
- University of Greenwich
- University of Oxford
- University of Oxford;
- University of Plymouth;
- University of Sheffield;
- University of Warwick
- 16 more »
- « less
-
Field
-
industries: in-car systems, medical devices, phones, sensor networks, condition monitoring systems, high-performance compute, and high-frequency trading. This CDT develops researchers with expertise across
-
language model (LLM) technologies to create advanced, multimodal predictive tools for plant health monitoring. Using imagery from RGB cameras, drones, satellites, and multispectral and hyperspectral sensors
-
costs will also be provided. Overview This project explores the design of scalable and privacy-preserving AI systems for pervasive healthcare environments, where embedded devices and dynamic sensor
-
: Identify responder needs; enhance optical detection; develop SAR indicators; fuse multi-sensor outputs using probabilistic methods; quantify performance under realistic cloud scenarios; validate across
-
, enhanced sensors, anti-fouling protection and much more. Going beyond existing work using expensive fabrication of planar 2D metamaterials, this project explores routes to use nano-assembly to create 3D
-
project’s focus is to: Conduct cutting-edge experiments to investigate how surface texture affects seal performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with
-
capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
-
-critical decisions in real time. These systems rely heavily on sensor data (e.g., GPS, pressure transducers, image processors), making them vulnerable to stealthy threats like False Data Injection (FDI) and
-
for path inference; introducing sensors; behaviour classification; resource-constrained active-learning; other IoT applications; microbattery development and field experiments and flight path analysis
-
performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling