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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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Force Microscopy. Electroactive biomaterial experience, including electrochemical characterisation and synthesis. Expertise with advanced graphing and/or data analysis software (Prism, Origin Pro, Matlab
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visualization environments Optimize scene graphs, memory management, asset streaming, and runtime performance Contribute to research proposals and peer-reviewed publications Generative AI Integration Generative
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text leveraging fine-tuned Vision-Language Models (VLMs) from WP3, supporting zero-shot reasoning and scene-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference
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, and clinical safety datasets Implement graph-based retrieval-augmented generation (RAG) methods to enhance knowledge extraction and information synthesis Develop cross-pathway analytical methods using
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knowledge graphs, rules, and process understanding, with implications across sectors from ecology to infrastructure. 4. Theme 4 (“Communities”): Green and Resilient Communities and Entrepreneurship
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, Lingnan University is transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https
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-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference speed, compute efficiency, and scalability with concurrent agents. Maintain high software engineering
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leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/ . Applications are now invited for
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Framework (IMF) based on ISO 81346, the research proposes the extension of IMF with an explicit temporal aspect, enabling time-aware system modeling and the creation of a unified system knowledge graph