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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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algorithms is desirable. About the Department This post is within the School of Engineering and Materials Science, a large School with 108 academics, more than 250 PhD students and over 2500 undergraduate
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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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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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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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to numerical simulation algorithms? Then apply now to join our team of theoretical researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere of play: As a