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Singapore’s AI-for-Science ecosystem. The candidate is expected to conduct the following research works Perform first-principles calculations on bulk systems, surfaces, and nanostructures as required. Develop
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. Publish research findings in top-tier IEEE journals and present at leading conferences. Collaborate with the team to develop innovative solutions for improving the reliability of power electronic devices
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Propose and develop state-of-the-art methods to overcome existing problems. Train and evaluate the models and systemically compare them with recent models. Prepare papers and reports. Develop systems based
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and validate a prototype microscope with enhanced sensitivity and contrast, evaluate label‑free and fluorescence imaging modes, and develop robust hardware/software workflows for low‑light measurements
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contribute to the overall development of the team and project. Additional responsibilities include supporting team operations and taking on related tasks as needed. Job Requirements: Preferably PhD in computer
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, including deep neural networks and physics-informed neural networks, to analyse large datasets from gyrokinetic and fluid simulations of plasma turbulence Develop and train reduced-order models that capture
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Singapore’s AI-for-Science ecosystem. Key Responsibilities: The candidate is expected to conduct the following research works Develop and implement the "AI+Physics" discrepancy modeling framework to predict
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the research and support team that conducts clinical trials and manages day-to-day operations. Key Responsibilities Clinical Trial Innovation and Excellence Development of innovative clinical trial
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, teaching, and student engagement in AI-for-Science courses and seminars. - Support the development and deployment of AI-driven tools for High-Performance Computing (HPC) applications. Qualifications
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imaging) and development of novel imaging techniques (nuclear and molecular imaging, computational imaging, etc). With the formation of the National University Health System (NUHS), both clinical and