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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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). Experience with qualitative research methods (e.g., ethnography, qualitative interviews, focus groups, or participatory design). Knowledge of sustainability issues impacting the medical devices industry
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safety standards and contribute to safer adoption of electrified transport. Reasons to study: Experience in an industry with high prospects of employability. Access to cutting-edge coating design
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representations are developed. In particular, the project will support designers to achieve driver and passenger experiences that surpass current best-in-class benchmarks. Beyond the automotive sector, the project
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, this interdisciplinary project will couple mathematical models of earthworm movement, stochastic models of the measurement process and designed experiments to improve earthworm detection. Project This project will work
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generally make the vehicle a special place to be. The project will treat the experience of tranquillity as a phenomenon that can be measured and influenced. Attention to design contexts and design processes
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the combined themes of human-computer interaction and critical computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots
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is expected to soon be able to diagnose diseases occurring outside the retina. OCT images can be aberrated by the eye itself and imperfect optical design. Ocular imaging with adaptive optics promises