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Field
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candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex data
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to test the current algorithm and inform development of future algorithm refinements aimed at supporting diabetic foot ulcer (DFU) prevention through identification of temperature differences of > 2.2°C
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and Applications of Algorithms” at the Faculty of Computer Science. The position is limited to six months and is planned to be filled from 01.10.2025. Your future tasks: Participation in research
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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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. 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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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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, with experience in algorithm development. Confident coding skills and familiarity with modern coding workflows and best practices. Excellent verbal communication skills and the ability to engage
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applications for monitoring and managing aquatic environments under study, the Mekong river delta and the Forth river system Develop, test and apply algorithms for the processing and analysis of satellite data
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both the algorithms for robot co-design, and the real-world evaluation of the designs that emerge. You will investigate evolutionary algorithms to explore creative new hand designs, and reinforcement