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Interview Motivated in learning new methodologies and applying new knowledge Essential Interview Knowledge of the approximate Bayesian machine learning (e.g. MCMC) (assessed at: Application form/Interview
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Early-stage failure prediction in fusion materials using machine learning
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and techniques. In addition, you will combine study and work-based learning to achieve the National Apprenticeship Standard - Laboratory Technician Level 3, which will span the full two years of your
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A Machine Learning Enabled Physical Layer for 6G Radio Systems
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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
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). Modelling tools used will vary according to application but are likely to including process simulation using Population Balance Modelling, DEM simulations and Machine Learning Approaches. Main duties and
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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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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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global castings industry. The AMRC Castings Group is a leader in advancing casting technologies and techniques. Our team provides advanced casting expertise, including computer process modelling, design
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-resolution imaging and reconstruction of neural tissues (see https://ist.ac.at/en/research/siegert-group/). Leveraging computational tools such as machine learning and topological data analysis, we will