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artificial intelligence. The research will provide valuable experience in game development, user-centred design, accessibility research, and experimental evaluation. The project offers access to specialist
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candidate will design algorithms that identify suspicious model updates, reduce the influence of compromised UAVs, and preserve useful learning from honest UAVs operating with different data and unreliable
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This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a
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other inside a tissue. In this project, you will build interpretable-by-design machine learning models for biological data that offer biological insights in a direct way. Such models will be applicable
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of electrodes containing recycled material. Electrochemical evaluation of recycled cathode and anode materials. Development of design-for-recycling principles for future battery technologies. The project will be
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application. The project aims to change this by realizing pulsed DNP on a chip. What you would be doing PhD 1: • explore architectures and design the pulsed-DNP chip • oversee chip manufacturing and
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design of research and creative projects. Assists in short- and long-term planning and project goals. May assist with research and creative proposals and dissemination of project findings. Additional
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be removed once the position has been filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify
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learning paradigms. The framework will support rapid prototyping, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms
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at a time, with each cycle of design, synthesis and testing taking months. This project will pioneer a faster way to do this: new chemistry methods that let around 100 candidate compounds be made