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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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%). The position will be offered for three years and will have as topic the classical emulation of quantum algorithms for the simulation of complex quantum systems. The position will be based at the Institute
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the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization libraries in R or Python. * Experience with GitHub, conda environment and
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization
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computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain