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. Exposure to neural-symbolic algorithms for transforming intent into conformant security or safety policy and/or enforcing security controls is optional but beneficial. Research will also give the opportunity
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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
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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representation. Key aims include improving the generalizability, interpretability, reasoning and causal grounding of these models, developing new optimisation algorithms with biologically meaningful regularisation
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Your Job: Design and development of an in-house X-ray beamline for long term operando investigation of chemical hydrogen storage reactors Unravelling of relationships between catalyst structure and
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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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and qualification aiming to develop a disruptive laser technology to address realworld applications in health science and quantum technology. The basic concept relies on the exploitation of low phonon
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-Making and Route Optimisation: Develop adaptive algorithms within a bias-aware ensemble Kalman filter framework to propose alternative flight paths dynamically. The system will aim to maximise safety and
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and reliability. You will integrate, adapt and develop methods (using packages such as BioSPPy) for the processing and analysis of physiological signals measured for determining deception. The project
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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication