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Field
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–structure–corrosion relationships; Develop and optimize material-specific LPBF parameters and post-processing treatments to improve corrosion resistance; Evaluate how reduced support structures and adaptive
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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 molecular and cellular systems. Duties & Responsibilities • Develop and benchmark AI/ML methods for TCR design, including template retrieval, CDR3 optimization, off-target-aware selection, and structure
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NTU’s global reputation for excellence in robotics and AI. Key Responsibilities Design and implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms
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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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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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lithographic techniques to etch novel lattice patterns Perform optical characterizations of structures using various optical spectroscopy Collaborate with theoretical researchers in the design and optimization
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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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manufacturing, driving innovations in semiconductor manufacturing, micro-optics, photonic devices, advanced packaging, and functional materials through process development and design optimization. ● Lead
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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