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Field
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the largest optical telescope in the world and will develop skills in machine learning, observational and theoretical astrophysics. For more information on this project please contact s.littlefair
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of data from in-Situ AM Process Monitoring tools, machine agnostic algorithms will be generated for quality control. Knowledge transfer of the methods developed onto industrial machine platforms will be a
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, advanced statistical methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and
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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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. There are activities across the University that are potential collaborators for work in ICNS, including Machine Learning (in the Department of Computer Science), Cognitive Robotics (in Computer Science and Electrical
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Development of Digital Twin Models for Real-Time Condition Monitoring of Electrical Machines in Electric Vehicle Applications School of Electrical and Electronic Engineering PhD Research Project
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analytics techniques (machine learning) for process control and optimisation. In this project, you will focus on achieving metamaterial behaviour through phase control within the additive manufacturing build
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-qualification research experience. Relevant areas of research include computational chemistry, structural biology/bioinformatics, statistics, machine learning, computer science or mathematics. They will have a
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Forecasting the Future of Biodiversity: Cutting-Edge Approaches to Population and Community Dynamics
: How can tools like passive bioacoustics revolutionize wildlife monitoring? We offer cutting-edge training in statistical modelling, machine learning, and ecological forecasting, and our lab works across
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data gaps by combining process simulation (e.g., Aspen software) with machine learning techniques. By developing accurate, large-scale life cycle inventory data using enhanced digital tools like deep