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representation, knowledge engineering, linked data. About the role The successful candidate will join the Distributed AI (DAI) group in the Department of Informatics, King’s College London. They will carry out
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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Engineering or a related field. In this role, the selected candidate will be responsible for designing, developing, and optimising algorithms for processing and analysing signals in real-time applications
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Learning, Algorithms, Noise Handling (Error Correction/Mitigation), and Verification. These roles are part of the Quantum Software Lab (QSL, link: https://www.quantumsoftwarelab.com ), in collaboration with
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both the algorithms for robot co-design, and the real-world evaluation of the designs that emerge, as well as providing your own research contributions. Your specific role will vary depending on project
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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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, including: Robot Learning: Creating algorithms that empower robots to learn autonomously from interactions and adjust to new tasks. Manipulation: Enhancing techniques for precise and adaptable object handling