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Field
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machine learning and AI methods to develop clinical decision support systems for high-flow nasal cannula therapy. The project: Concerns around the possible negative consequences of delayed escalation
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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About the project: Machine learning accelerated electronic transport calculations for complex materials Supervisor: Prof. Neophytos Neophytou, University of Warwick Advancements in materials
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide
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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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Application documents: 1) Brief cover letter, explaining your motivation for applying, 2) Detailed curriculum vitae (including your email address), 3) Complete transcript of grades from all your university-level studies. We do not ask for more information/documents at this point (but you can...
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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consider task success, generalisation, reliability and computational efficiency. The goal is original research for leading machine-learning, computer-vision and robotics venues. The successful candidate will