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for light-based technologies’ with Associate Professor Jenny Malmström (University of Auckland) ‘Tiny droplets with big potential: designing stimuli-responsive liquid micro-structures for sustainable
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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In the process of laser shock peening (LSP), metallic structural components are hit by controlled laser pulses. The sudden vaporisation of material at the structural surface creates large magnitude
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a focus on meat and dairy promotion. In partnership with Adfree Cities, the student will investigate: (1) the link between advertising exposure and mental health using large-scale secondary data and
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify
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attention to detail, diligence, and ability to do most work independently. The desired skills include being able to review and structure a literature base, deal with large amounts of data in different forms
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 2 months ago
to identify opportunities for British Sugar as a case study which can then be applied across a wide range of dispersed industrial sites. These sites are those that might not benefit from large infrastructure
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
of an accurate and generalisable density Equation of State model (EoS). This is especially challenging near the critical point and the Widom line, where there are large gradients in fluid properties. This project
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This project explores the use of state-space models (SSMs) for sequence modeling in large language models (LLMs), focusing on their CMOS-based hardware implementation. The PhD candidate will develop energy