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functions, molecules, and technologies. We seek candidates who combine fundamental understanding of biological and biochemical systems with quantitative, computational, and engineering approaches to design
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adaptive, personalised, and data-informed learning experiences. The project combines educational development, generative AI tools, learning analytics, experimental implementation, and quantitative analysis
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cooling, and two-phase cooling for very high heat fluxes. You will develop and use Computational Fluid Dynamics models in combination with analytical and reduced-order models, and contribute to publishing
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of Engineering programme as Associate Professor in AI and Computer Vision. You will play a central role in educating future engineers, combining deep technical expertise with close interaction with students in a
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to molecular hydration. The student will develop experimental methodologies and combine these with state-of-the-art characterization techniques, including Magnetic Resonance Imaging (MRI), Nuclear Magnetic
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programmes. A clear, well-developed and viable strategy for future high-level research. A track record of good citizenship in the wider academic community, combined with a commitment to contributing to a