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systems and ultimately aims to broaden their uptake for urban energy supply. Working as part of a multi-disciplinary project team, featuring engineers, hydrologists, numerical modellers and policy liaisons
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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Research Fellow in AI for Healthcare (1 FTE) – ArcHub ICUSafeNotes-School of Computer Science 011287
breakthroughs into commercial healthcare solutions. In the ICUSafeNotes project, we are conducting research and development of multimodal machine learning models that includes ICU note summarisation and analysis
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experience in data-knowledge fusion-driven dynamic modeling of complex structures, specializing in uncertainty quantification of nonlinear systems and intelligent model order reduction methods, with at least
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models for children. College / Directorate College of Engineering, Design & Physical Sciences Department Department of Mechanical and Aerospace Engineering Full Time / Part Time Full Time Position Title
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parallel, a numerical model representative of the developed materials will be created. Work plan: The work plan foreseen for the research grant has been designed to support the experimental research
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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, two-way pushdown automata, and related models of computation) is a plus but not essential: candidates with a different background are also encouraged to apply. Full details of the duties and selection
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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
variety of research methods, such as scientific experimentation, literature reviews. Analyse and interpret data Contribute to developing new models, techniques and methods Disseminating research results
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to research funded by the NIHR Health and Social Care Delivery Research (HSDR) to explore how the employment and deployment models of additional roles staff in primary care impact on staff and patient