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Field
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extreme weather to cybersecurity threats. Working within the LDTRC, you will undertake a range of research tasks, including: 1) Defining the ontology and knowledge graph architecture for a scalable digital
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knowledge of deep learning architectures and, in particular, Large Language Models (LLMs). Knowledge is valued both in advanced prompt engineering techniques (e.g. few-shot learning, chain-of-thought
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for key stored-product pest species using long-read sequencing and advanced annotation methods, enabling comparative genomic analyses to determine how variation in gene content and genome architecture
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air temperature maps • Develop and train Graph Neural Network (GNN) and Long Short-Term Memory (LSTM) architectures to model complex spatial and temporal dependencies in urban microclimate data
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algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
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data. The resulting datasets will form high-dimensional spatial atlases that connect molecular processes to cellular interactions, tissue architecture, biomechanics, and organism-level function
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extreme weather to cybersecurity threats. Working within the LDTRC, you will undertake a range of research tasks, including: 1) Defining the ontology and knowledge graph architecture for a scalable digital
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, sensors, switch, electrochemical transistors, with scalable architectures for real-world applications. The School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang
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, sensors, switch, electrochemical transistors, with scalable architectures for real-world applications. The School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang
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) Lightweight DLT-backed credential gateway architecture for constrained IoT devices ii) Prototype implementation based on existing SSI and DLT components iii) Scalable evaluation environment and a complete