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. The successful candidate will develop high-performance photonic devices based on lithium niobate, silicon photonics, and heterogeneous material platforms, with emphasis on electro-optic modulators, low-loss
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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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: Development of novel designs and mechanisms for shape-morphing structures Development of models for sensing and control in shape-morphing systems Experimental implementation of designs Engaging in scientific
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We are looking for a Research Fellow (RF) to work with Prof. Ning Yan (Department of Chemical and Biomolecular Engineering, NUS). Project Overview: This project aims to develop catalytic processes
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leading centres for photonics research. The successful candidate will join a multidisciplinary team developing advanced III-V semiconductor materials and integrated optoelectronic devices on silicon
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Institute. Working closely with the Lotfollahi Lab – leaders in generative AI and foundation models for spatial and single-cell genomics – you will develop and apply state-of-the-art machine learning
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to undertake complementary, ambitious two-year research projects in Statistical Ocean Acoustics. The programme will develop a deeper understanding of how spatial and temporal variability, coherence and
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Assembly Job Quality Inspection”. The role will focus on research and development of AI algorithms for defect detection, image/video analysis and understanding Key Responsibilities: Develop artificial
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analyses of single-cell and spatial omics to advance precision medicine. Dr Chen’s research team develops AI algorithms for spatial and single-cell omics, integrates publicly available datasets into a
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that drive weediness evolution, crop stress tolerance, and breeding improvement. You will help analyze genomic, transcriptomic, phenomic, and physiological datasets from corn, snap bean, soybean, and waterhemp