Sort by
Refine Your Search
-
. To fill in this gap, in collaboration with industrial partners, the research will develop novel Machine Learning and Computer Vision methods for detecting and localising. These will be used to develop
-
AI for Multi-modal Healthcare School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Chen Chen Application Deadline: 30 April 2025 Details A 3.5-year funded PhD
-
Improving Deep Reinforcement Learning through Interactive Human Feedback School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Bei Peng, Dr Robert Loftin Application
-
Computational imaging: seeing beyond the capabilities of conventional optics School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Andrew Maiden Application Deadline
-
, has been shown to have a synergistic effect in increasing the toughness of composites in some cases. This research is following the recently started research program on understanding the effect of nano
-
. This paves the way for the application of MPC to large-scale systems, since the computational bottleneck is removed. The basic challenge is how to coordinate the distributed decision making of agents so that
-
electromagnetic design. We will explore advanced topologies for mmwave metasurfaces, design novel reconfiguration mechanisms, and develop intelligent algorithms to optimize scattering characteristics in real-time
-
collaborative programme of research funded by the Aerospace Technology Institute (ATI) with several Industry partners, including Airbus, GKN and Renishaw. Critical for the implementation of additive manufacturing
-
processing, data analysis, data-driven modelling, optimisation and computation algorithms, machine learning models and neural network structures, as well as strong skills and experiences in computational
-
hardware-in-the-loop (HiL) techniques and ML algorithms for the accurate and on-time detection of faults, so that failures can be prevented by alerting the end-users and diagnosticians during periodical