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Overview This post is funded by the Quantum Computing Hub (QCI3) supported by the Engineering and Physical Sciences Research Council (EPSRC). The QCi3 Hub is part of Phase III of the UK’s Quantum
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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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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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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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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