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across records. Develop a cloud-based verification platform for digital data collection and real-time analytics. Develop and apply non-destructive testing (NDT) methods and data-driven approaches
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packages. Maintain high software engineering standards through rigorous testing, version control, clear documentation, and continuous improvement of development infrastructure (e.g., CI/CD, Docker, cloud
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building energy models. The role will focus on participating in the development and implementation strategy of a cloud AI-based framework to perform business valuation. Key Responsibilities: Develop new CFD
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, or equivalent PPLs. • Strong track record of publications in peer-reviewed journals commensurate with career stage. • Proficiency in Python and/or R; familiarity with high-performance and cloud computing
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techniques that enable scalable deployment on cloud, edge, and robotic platforms. The Research Fellow will contribute to the University’s mission by conducting high-impact research, developing innovative
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in and manage the research project with Principal Investigator (PI) to ensure all project deliverables are met. Derivation of closed-form theoretical latency and timeliness expressions for cloud-hosted
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such as R/Python/Java or similar languages, and familiarity with Unix-based platforms is advantageous Experience working in cloud environments (e.g., AWS) is beneficial High motivation and willingness
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standards through rigorous testing, version control, clear documentation, and continuous improvement of development infrastructure (e.g., CI/CD, Docker, cloud-based services). Carry out Risk Assessment, and
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analytics-driven research questions that lead to high quality publications. Experience working in interdisciplinary teams spanning clinical, wet-lab, and computational research. Familiarity with cloud
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during academic training, with basic knowledge of cluster usage or cloud-based AI tools More Information Location: Kent Ridge Campus Organization: Faculty of Science Department : Physics Job requisition ID