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develop and optimize scientific and engineering applications leveraging high-speed network capability provided by the Energy Sciences Network or run on next-generation high performance computing and data
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The ECE Department at NUS is seeking a Research Fellow to support advanced research in Backside Power Delivery Networks (BS-PDN) and advanced semiconductor packaging. The successful candidate will
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for existing commercial products. The work will involve numerical investigation of two-phase flows over louvre panels and experimental verification as well as optimal design by using neural network techniques
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photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced modelling and optimization techniques, this research aims to identify optimum
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, fabrication, optimization and experimental characterization of polaritonic waveguides, polariton lasers, cavity/waveguide networks, and polaritonic circuit elements. The role includes developing and operating
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, bioRxiv 2026, doi: 10.64898/2026.07.30.741759) for biological systems. You will lead a computational research project extending DMMSs from population-level to single-cell data, combining neural networks
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and networking technologies. Key Responsibilities: As an integral part of the project, the Research Fellow is expected to: Design PIC components and integrate SNSPDs with photonic integrated circuits
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or papers. Knowledge of network placement optimization for various topologies, e.g., Erdos-Renyi random network, scale-free, small world, etc, will be advantageous. key Competencies: Understand existing
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) working on a wearable sensor development project. This project aims to develop a Wearable Sensor Network that integrates wireless, miniaturized sensors to measure physiological parameters across multiple
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process of continuous germplasm improvement, discovery trait research and methodology optimization to reach greater breeding efficiency. The general research technologies/methodologies and approaches