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project - “Oracle complexity bounds of first-order methods for nonsmooth optimization with nonconvex function constraints”. They will be required to conduct theoretical analysis, algorithm implementation
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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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This postdoc will work under the supervision of Dr. Guanyi Wang in ISEM at NUS to explore cutting-edge algorithms, derive rigorous theoretical guarantees, and implement numerical simulations
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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
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programming, distributionally robust optimization, optimal transport, or reinforcement learning is highly desirable; • Programming skills in Python are desirable, especially experience with numerical
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surface waters, preferably in estuaries; Experience in fieldwork and processing of oceanographic data (in particular CTD data); Knowledge of MATLAB or Python; Experience in numerical modelling; Fluency in
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, and Large Language Modelling (LLM). Conduct extensive numerical experiments to validate and evaluate the performance of the proposed models. Present research results as academic papers and reports
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with demonstrated ability to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph
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include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and full-scale structural testing of sleepers under static and
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and validate railway sleepers made with UHPC. The work may include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and