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background in machine learning, manufacturing, characterization, and testing of novel high performance multifunctional materials. During the project, you will conduct independent research within the designated
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly
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We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate Change and
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The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model that can
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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The role The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model
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transport calculations and programming. Expertise in quantum transport and using machine learning algorithms for first principle calculations will be distinct advantage. You should be able to work
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Imperial College London and Imperial College Healthcare NHS Trust (ICHT). The project aims to transform the clinical use of electroencephalography (EEG) by developing and validating machine learning
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publications. Have experience analysing AUV, BRUV or other marine video datasets; Demonstrate advanced GIS capability (ArcGIS Pro or QGIS) is essential, as is confidence in applying machine-learning approaches
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systems. You will also explore the cutting-edge application of AI and machine learning in channel prediction. As an active member of CWI, you will contribute to our world-class research output by publishing