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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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research on shipping and port operational optimization, maritime decarbonization, data analytics, and the development and application of novel methodologies (including LLM-based prediction and optimization
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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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, 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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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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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
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optimization using tools such as Lumerical FDTD, or equivalent simulation platforms. • Analyze device physics and process–performance relationships, collaborate with multidisciplinary research teams, and
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for Science with inadequate attention and support. This proposal addresses the gap by focusing on the development of optimized implementations for AI for Science workloads. Bespoke communication and computation
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the conversion of CO2 into value-added chemical products. Roles & Responsibilities: • Design, synthesize, and optimize catalysts for CO2 hydrogenation to useful chemicals. • Conduct catalytic testing