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Field
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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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. Develop and optimize radical coupling reactions, including reaction design, selectivity, efficiency and substrate-scope evaluation. Plan protecting-group strategies and control chemoselectivity
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, payloads, linker-payloads and other ADC-related molecules. Develop and optimize amide-bond formation and conjugation reactions, including coupling-reagent selection, protecting-group strategies
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The successful candidate will work with Asst. Prof. Shen Shuting on combinatorial inference under a project on "Post-learning inference for near-optimal discrete structures". The main
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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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, 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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transcriptomics datasets, and of paired molecular and functional measurements (e.g., electrophysiology), as well as optimally leveraging integration with existing genomics datasets. The role is focused
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couplers, and packaging interfaces using commercial photonic design tools. Perform optical simulations and tolerance analyses to optimize coupling efficiency, bandwidth, alignment tolerance, and packaging