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sustainability challenges through research and active contributions to standardisation efforts. Your role This fully funded PhD position focuses on exploring and developing hybrid quantum-classical algorithms
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discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Swarm intelligence Algorithmics Parallel
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Computer Science, Civil Engineering, or any related engineering discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation algorithms Machine
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of public data. Key challenges include balancing privacy guarantees with utility, designing efficient algorithms for real-world applications, and assessing security and business implications in practical
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positioning, navigation, and timing (PNT) applications for the next generation satellite systems Developing innovative solutions and algorithms to integrate communication and sensing or communications and PNT
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: Software engineering practices for machine learning Define quality and security principles for machine learning systems Design and implement technical testing algorithms to assess these systems in real-world
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application of machine learning algorithms to automatically classify freshwater benthic diatoms at the species level and quantify key morphological traits. These advancements aim to improve ecological