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• Information-theoretical analysis of entanglement-supported classical communication, • Encoding protocols for entanglement-assisted classical communication, • Protocols for interleaving transmission in networks
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on the physical layer design of wireless communication systems and explore enabling technologies for 6G and beyond wireless networks. Applicants must hold a PhD degree in electrical/electronics engineering
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The successful applicant will have (or be near to completion of) a PhD in Computer Science with expertise indeep neural networks, preferably with expertise in any of the following subfields: signal processing and
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management Cognitive radio or adaptive communication systems, including dynamic spectrum access, band selection Heterogeneous network architectures, including terrestrial and non-terrestrial networks Deep
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Excellent command of advanced statistical methods, such as network analyses, using the R programming language Strong publication record relative to the career stage, demonstrating research excellence and
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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About the role The University of Leicester is proud to be part of the UK Nuclear Deterrence Network, a collaborative initiative with King’s College London and the Royal United Services Institute. As
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neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets
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-omic, multi-context gene regulatory networks (GRNs) from large-scale single-cell datasets. We are pioneers in GRN reconstruction from single-cell multi-omics, including: Causal GRNs from Perturb-seq
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fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results