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Field
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
: Algorithm Validation and Use Case Demonstration (Months 27–36): This WP will first develop an integrated hardware–software testbed to systematically validate the performance of proposed solutions under
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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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volumes in a reliable, repeatable, and automated way. This project aims to establish a data-driven, adaptive framework that develops artificial intelligence tools, integrated with advanced geostatistics
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; Develop system architecture and training strategy to enable the FM to learn from heterogeneous MRI data in terms of data source purpose and physical location in the scanner; Develop efficient techniques
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Are you eager to research and develop Visual Analytics techniques for Event Sequence exploration and analysis? Are you curious how to combine and explore the synergy between Visualization and
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open
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to train tomorrows leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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, efficient and context-aware, creating the foundations for the next generation of wearable and augmented reality platforms. The research focuses on developing novel ML methods that learn from limited resources