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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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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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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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examining modulation of the tumor microenvironment and obesity-related colorectal cancer (CRC) disease progression using tissue-engineered patient derived xenograft (PDX) CRC models validated through
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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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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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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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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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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