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carrying out mentor-guided experiments for method development, optimization, and validation to assess performance characteristics such as accuracy, precision, analytical measurement range, limits
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stage of the biomonitoring project associated with the appointment. Analytical method development and optimization – You may gain experience designing and carrying out mentor-guided experiments
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The Duke-NUS Metabolomics Lab is a leading metabolomics core and research facility in Singapore, actively contributing to numerous projects aimed at uncovering disease mechanisms through advanced
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expertise in discrete choice modelling, statistical modeling, traffic simulation, machine learning, and optimization techniques. • Strong expertise in discrete choice modelling, statistical modelling, and
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for biocementation Perform numerical study of the model test. Analyze and interpret data to make informed recommendations for costal protection system design and optimization Writing and publication of results in peer
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, developing complex numerical models and validating them against datasets generated by collaborators. The candidate will use surrogate modelling and data-centric approaches to complement simulations
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, with expertise in dynamic/data-driven modeling, optimization, Aspen, COMSOL, or CFD b. Techno-economic analysis (TEA) & life-cycle assessment (LCA) for chemical, energy, or biomanufacturing processes
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, and optimize multimaterial LPBF processes, integrating in-situ monitoring, process parameters, material combinations, and resulting microstructural and structural outcomes. Design and optimize
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candidate will participate in a NIH grant-funded project on optimism and longevity. The research involves conducting both primary data collection exploring new methods for measuring optimism (or other
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work at the interface of micro/nanofabrication, point-of-care (POC) development, and biomedical diagnostics. This role offers a unique opportunity to contribute to the design and optimization