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Field
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research in digital and high-frequency electronics, embedded systems, control, and communication, utilizing cutting-edge reconfigurable computing and sensors. The aim is to develop next-generation
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication-efficient and
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through simulations and with physical drones in mock search-and
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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/field personnel in research. Initial studies will focus on burn wounds, improving healing and assessing multiple wound factors using imaging and sensors. What you need to know Salary: Compensation will be
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novel photonic techniques such as time resolved single photon technologies, spectral imaging, and optical fibre sensors to tackle clinical/biomedical challenges and other real world applications. Our work