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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 36 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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Join our dynamic, multidisciplinary team as a Research Associate and make a transformative impact in scientific machine learning and digital twins for healthcare innovation! This role focuses
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. Lead the University into the AI Future Whether it’s the way we work, learn, discover or make decisions, artificial Intelligence is changing society. At the University of Manchester, we’re positively
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the centre. Successful applicants will have (or be about to obtain) a PhD in computational biology or computer science, with knowledge of multimodal spatial omics data integration and machine learning
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cutting-edge machine learning methods for spatial omics and for multi-modal data integration. The post-holder will also collaborate on the development of new computational methods to support the CoRE’s
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an expert in the use of advanced statistical inference and machine learning methods for the analysis of omics datasets. You will work with a team of data scientists in Manchester and Oxford to create tissue
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. Lead the University into the AI Future Whether it’s the way we work, learn, discover or make decisions, Artificial Intelligence is changing society. At the University of Manchester, we’re positively
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and enabling commercial deployment. The work will integrate model based design of experiments, machine learning, hybrid and kinetic modelling (digital twin development), process design, simulation and
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, Landsat), and machine and deep learning techniques to quantify historic dynamics of small-scale irrigated agriculture and develop an interactive irrigation mapping toolbox for government and end users
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. We plan to use machine-learning to identify markers of listening intentions from data collected via sound recordings, photographs, ecological momentary assessments (EMA), and passively monitored