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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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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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, 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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1. A PhD degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Systems Engineering, etc. 2. The candidates should have strong math, modeling, programming, and
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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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, 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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key role in driving high-impact research, developing innovative objectives, and formulating proposals within cutting-edge fields, including Computer Vision, Digital Healthcare, AI Optimization, and
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://dimag.ibs.re.kr/ Successful candidates for the research fellowship positions will be new or recent PhDs with outstanding research potential in all fields of Discrete Mathematics with emphasis on Structural Graph
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Singapore on a dense plasma focus device which also produces gamma-rays due to plasma instabilities. Requirements: Essential PhD in Physics Engineering or a related field. Demonstrated experience in pulsed
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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security