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Field
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic
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Application Deadline 15 Jan 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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identification context, while promising for network-level monitoring, has been largely underexplored. To this end, the project will explore the application of the next generation of deep learning algorithms, e.g
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for communication and computing in highly dense cellular networks and for infrastructure-less wireless services. Successful applicants will work on algorithms and techniques to make Safe Machine Learning available
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, the project will develop algorithms for ecological sensing, adaptive motion planning, and energy optimisation under real-world constraints. Scaled experiments and high-fidelity simulations will validate system
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for medical time-series. Cutting-Edge Resources: Benefit from state-of-the-art High-Performance Computing (HPC) facilities, unique multimodal datasets, and advanced wearable technologies. Global Collaboration
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
such a promising technology, the centralised and resource-intensive nature of current LLMs conflicts with the constraints of aerial 6G networks in terms of limited computation, energy, and communication