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Field
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integration, low-voltage distribution-network modelling, optimisation-based power flow analysis, and standards development, producing impactful publications, open-source code, and datasets. Supervision and
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pipelines and failure mode analysis tools to analyze VLM performance across reasoning dimensions Prepare technical reports, publications, and industry-facing deliverables Mentor student assistants Candidates
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This PhD project focuses on developing formal methods and knowledge representation techniques for the modelling and analysis of complex manufacturing and intralogistics systems, such as highly automated
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and usable analytics outputs. Key Responsibilities Applied Research & Development Perform clinical needs assessment and workflow analysis for organisational innovation transition, focusing on but not
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applications. Key hands-on training components include: Spectroscopic techniques including UV-Vis, FTIR, Raman, & Mass spectral analysis Development of structured databases for orthogonal characterization
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, to pilot plant scale production involving centrifugation, clarification, recovery and separation of supernatant, and drying process. Support AI‑enabled data analysis, including collaboration
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data architectures and tools for automating data analysis. Relevant software platforms include Matlab and Python. Develop physics-based computational models (e.g., finite element analysis) to complement
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experience with DNA extraction and PCR amplification Demonstrated experience performing qPCR assays for nucleic acid quantification and molecular analysis, including troubleshooting Demonstrated experience
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of healthcare technologies, resource management, and healthcare business practices in Singapore. Experience in healthcare workflow analysis, automation implementation, and healthcare metrics. Strong analytical
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clinical needs assessment and workflow analysis into engineering requirements for organisational innovation transition, focusing on but not limited to community and aged care settings, nursing homes