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The Economics Programme in NTU’s School of Social Sciences seeks a Research Fellow. The research develops reliable instrumental variable (IV) estimation/inference method and machine learning
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validate data-driven methods that combine production data, predictive and state-estimation models, uncertainty-aware learning and constrained optimization to improve process consistency under process drift
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response using conventional methods alone. Unknown external forces and torsional response can instead be estimated using methods such as convex optimization or Kalman filtering. These torque estimation
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intelligence methods to substantive questions in political science. We seek a scholar with expertise in machine learning, natural language processing, generative AI, computational social science, or related data
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econometric methods. Design and implement AI- and large language model-enabled decision-making agents and research frameworks. Collect, process, and analyse large-scale financial, blockchain, market, and other
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Medicine Course Title: Foundations of Mixed Methods Research Course Code: FMED 614 Estimated Number of Positions: 1 Total Hours of Work per Term: 0 Hiring Unit: Department of Family Medicine Course Number
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About the CDT Machine Learning has a dramatic impact on our daily lives built on the back of improved computer systems. Systems research and ML research are symbiotic. Modern systems research
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methods, and measurement uncertainty. Video processing, computer vision, automated event extraction, or behavioral observation. Controlled testbed development and field data collection. Preparation
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estimators and new methods for assessing sampling error when these standard conditions do not hold. The postdoctoral researcher’s work will involve both theoretical research, focusing on the properties
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mathematical foundations, particularly in linear algebra, optimisation, probability, and numerical methods. Experience in computer vision, computer graphics, computational imaging, or machine learning. Excellent