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-driven reusability assessment platforms integrating NDT data, machine learning models, and RFID-enabled traceability systems. Prepare and draft technical reports, conference/journal papers, and
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directly from experimental and process data, these models will enable a shift from iterative, trial-and-error fabrication towards predictive and data-driven manufacturing. We are seeking a highly motivated
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applied research on AI-driven and AI-enhanced industrial energy systems optimization modeling, material flow analysis, and supply chain analysis of industrial commodities and critical materials
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The AI-Driven Energy Chemistry research group at the School of Chemistry, Chemical Engineering, and Biotechnology (CCEB), Nanyang Technological University (NTU), Singapore, is dedicated
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and data-driven manufacturing. We are seeking a highly motivated Machine Learning Researcher to join a multidisciplinary team of fabrication engineers and AI specialists at the University of Southampton
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steel or aluminium structures Welding, fabrication, or construction automation Experimental structural testing and instrumentation Numerical modelling and simulation AI/data-driven methods for engineering
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directly from experimental and process data, these models will enable a shift from iterative, trial-and-error fabrication towards predictive and data-driven manufacturing. We are seeking a highly motivated
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programmability, network exposure APIs, service orchestration, O‑RAN, network slicing, and data-driven optimization. You have proven experience with AI/ML pipelines, including data processing, model training
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Research Associates/Assistants to support a diverse portfolio of research projects at the intersection of infectious disease modelling, Bayesian inference, AI, and public health. Projects span AI-driven
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Job Description Job Alerts Link Apply now Research Fellow (Operations Research) University-Level Unit: College of Design and Engineering Faculty/Department-Level Unit: Industrial Systems Engineering