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factors, and data provenance. o Develop data pipelines integrating BIM/IFC, schedules (4D), IoT/telemetry, procurement/ERP, and emissions factor databases. • Analytics and optimization o Apply data
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, hydrogen, ammonia, etc. Design the reciprocating engine experimental platform and perform engine testing Measure engine emission and conducted the species analysis Model the engine performance and emission
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materials. Experience in mechanical testing methodologies, including wear assessment, fracture strength evaluation, and fatigue testing, alongside chemical analysis techniques like ion leaching and
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qPCR, western blotting and other metabolic-related assays) To perform other related duties, incidental to the work described herein (such as conduct data analysis, ensure the validity and reliability
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administration Conduct quantitative and qualitative processing and analysis Conduct analysis of data and findings Project and data management Academic publication and report preparation Disseminating the outcomes
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qPCR, western blotting and other metabolic-related assays) To perform other related duties, incidental to the work described herein (such as conduct data analysis, ensure the validity and reliability
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model complex brain data. The ideal applicant will have expertise in either systems neuroscience or NeuroAI/machine learning, particularly in analysis of large-scale neural data. The group places a strong
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electrolysers or related fields. • Experience with large-scale electrochemical systems, including component selection, system integration, and process scale-up is highly desirable. • Proficiency in
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background/interest in time-series analysis, theoretical machine learning on networks, and high-dimensional statistics. Key Responsibilities: Take the lead in developing sub-projects (problem formulation
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technical and financial risk domains. Design, implement, and validate the LLM Risk Quantification and Insurance Support Engine, including model formulation, data analysis, and simulation of LLM risk scenarios