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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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challenges: the computational complexity of operating large-scale decentralized markets, the uncertainty from renewable generation, and ensuring that decentralized market outcomes remain operationally feasible
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. Investing in the prevention of wear particles generation is a way to tackle this issue directly at the source, which is particularly relevant for wafer handling. Silicon is a very complex material, undergoing
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AI for Earth Observation and Result Visualisation Supervisor Names: Prof. Yaxin Bi The PhD researcher will investigate enhancements of deep learning’s predictive capabilities by integrating domain
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to specific key questions: What is the role of the individual hydrogel components, i.e., mucins, proteins, salt and water, in the complex process of their network formation and function? Job description
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The SigCom research group of SnT, headed by Prof. Symeon Chatzinotas, focuses on wireless/satellite communications and networking. The research areas focus on the formulation, modeling, design, and
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This PhD is aligned with an exciting new multi-centre research programme on parallel mesh generation for advancing cutting-edge high