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: Design and implement models for a knowledge graph as part of an R&D team. Research methods and techniques for populating the knowledge graph. Develop models or algorithms to facilitate risk identification
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machine vision algorithms. The system will be designed with the physical constraints of remote fusion environments in mind, including radiation tolerance, restricted access, and the need for automation and
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maintenance, production efficiency, and quality control. While the benefits of ML are significant, its adoption also introduces risks such as data privacy concerns, algorithmic bias, model transparency issues
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KTP Associate in Machine Learning ( Job Number: 25000811) Department of Computer Science Grade 7: - £39,105 - £43,878 per annum Fixed Term - Full Time Contract Duration: 30 months Contracted Hours
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impactful and rapid change. The successful candidate will line manage, support, and develop Research Associates and PhD Students, as well as support computational research projects across the PBCI and
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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
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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
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novel contributions to the field of computer vision and deep learning in smart manufacturing. These novel algorithms will then be integrated on to a mobile robotic system that will inform the design and
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. 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
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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