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Field
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to apply advanced AI models in areas such as catalyst design, multi-scale modeling, and spectroscopic analysis. The Research Fellow will take on a significant role in machine learning theoretical energy
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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an emphasis on technology, data science and the humanities. We are looking for a Research Fellow to conduct AI for medicine research. The role will focus on developing foundation models to medical image
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computational materials science techniques (DFT, MD, machine learning force field modelling) with data-driven approaches. Work with team to design and implement high-throughput experimental workflows for rapid
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quantify high-throughput binding data. Examples of suitable backgrounds: Optical engineering, hardware-software integration, image analysis. Building quantitative models: Using high-throughput binding data
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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an emphasis on technology, data science and the humanities. The Nutrition, Metabolism and Health Programme is addressing one of the world’s most pressing healthcare issue: Over nutrition driven chronic diseases
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disease treatment through advanced Digital Twin technology. Based in the Department of Computing and Mathematics, you will lead the design and development of AI-driven models applied to complex healthcare
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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, and real-time human health coaching. CADENCE D-PHA also aims to incorporate AI-driven assistance for cardiovascular disease patients through digital health coaching by leveraging large audio models and