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communication technologies is driving the progression of modern AI. However, current efforts are predominantly concentrated on Large Language Models (LLMs) tailored for industrial applications, leaving AI
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crop datasets incorporating trait phenotypes, environmental descriptors and genomic information to investigate Genotype-by-Environment-by-Management interactions. Develop and apply mixed-model
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carbon air travel in Hong Kong”. They will be required to be involved real-time monitoring of the new biorefinery process for SAF production, signal/data analysis, AI-assisted modelling, sensor and data
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across the University of Oxford and the Oxford Liver Cancer Centre of Excellence to improve outcomes in HCC. You will oversee the preclinical models of liver cancer and administrative activities, in line
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, generating process, material, and structural data to support model development, validation, and process consolidation. Develop and apply physics-based and data-driven modeling frameworks to describe, predict
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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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generative modeling, with a focus on flow matching and related techniques. To produce publications in top conferences and journals. To offer guidance and assistance to any students involved in the project
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systems that integrate explainable on-device AI and small language models (SLMs) to support human operators in making faster, safer, and more confident decisions. You will collaborate with a
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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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these processes influence susceptibility to infectious and inflammatory diseases. We integrate state-of-the-art mouse models, high-dimensional immune profiling, single-cell genomics, and functional immunology