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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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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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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
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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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related to software development and research. Understanding of fundamental data structures and algorithms for designing and implementing efficient software and models. Familiarity with cloud platforms and
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. By integrating cutting-edge multi-agent systems, federated learning, and game theory, this project will develop sophisticated decentralised algorithms that enable autonomous vehicles (AVs
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, post-docs and interns collaborating across universities to build better algorithms, software tools and benchmarks to assess the safety of AI implementations at the software and hardware level. We
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This position is ideally suited to someone wishing to transition from a post-doctorate career in academia to commercial software and algorithm development. You are not expected to be an AI expert
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et al (2015). A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem. European Journal of Operational Research.
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mix of algorithm engineering and formal methods, alongside more traditional software engineering activities. This project involves developing software which is both mathematically rigorous, and