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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
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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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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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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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related to staff position within a Research Infrastructure? No Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean
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demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric methods to extract meaningful biological insights from multivariate data and complex GCxGC-TOFMS datasets
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background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software development, including Python, model integration, and system
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, output validation and reporting. Developing integrative strategies for a diverse set of data, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning
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on exploring what works and what doesn’t - in the care of people at the end of life. Learn more about the project here: NIHR Award Details. The study is led by Associate Professor Susie Pearce, who will also be
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on exploring what works and what doesn’t - in the care of people at the end of life: Learn more about the project here: NIHR Award Details . The study is led by Associate Professor Susie Pearce, who will also be