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Field
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access to unique multimodal datasets derived from prospective clinical trials, large-scale electronic health record (EHR) resources, medical imaging, and multi-omic profiling platforms, including genomic
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gradient risks (seawater seepage beneath cut-off walls), and simulate site-scale multi-layer reclaimed site responses over long-term equivalent periods. Project Leadership: Supervise junior researchers
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learning, large-scale model optimization, and generalization. To explore scalable optimization methods for large-scale, distributed, and multi-node collaborative training. To conduct theoretical analysis
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integration framework with Foundational Multi-Scale Data Processing, Temporal Relationship Intelligence, and Intelligent LLM-Powered Social Simulation and Decision Support capabilities, that leads
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, and AI-driven computational biology. The successful candidate will develop and apply innovative computational methods to analyse large-scale multi-omic datasets, identify mutational patterns across
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/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and eigenmode analysis for photonic crystals; terahertz/microwave far-field spectra measurements or near
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/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and eigenmode analysis for photonic crystals; terahertz/microwave far-field spectra measurements or near
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impact on rock / cementitious materials using established constitutive models (e.g. K&C, RHT). • Meso-scale modelling of multi-phases cementitious materials (e.g. aggregates, mortar, interfaces
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metallisation, and participate in industrial scale trials at Ionic Technologies. Candidates should clearly demonstrate how they meet the following criteria on their application: Have or be about to obtain a PhD
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Systems Lab (https://psl-ntu.github.io ) at NTU’s CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI workflows. Responsibilities