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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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and writing of research grant proposals. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a
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learning, dynamical systems, sequence generative models and world modelling. Emphasis will be on methods that design and implement new architectures for latent dynamic modelling to enable identification
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methods, including regression discontinuity designs, difference-in-differences, event study, instrumental variable, and related approaches. The role involves working with large-scale administrative
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• Possess a PhD in a related discipline (transportation engineering, operations research, computer engineering/science, or related disciplines) by December 2024. • Strong knowledge and
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, electoral and survey datasets, and estimate and evaluate advanced statistical models using methods including difference-in-differences, event studies, regression discontinuity designs, instrumental variables
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: Preferably PhD in computer science or related field. Expertise in computer programming Knowledge in machine learning and data science Proven research ability as evidenced through a portfolio of publications
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role in advancing the research agenda. Your responsibilities will include: · Perform research on computational modeling of EF-hand proteins · Perform method development for relevant systems of EF-hand
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successful candidate you will work with a team on Redesigning Digital Justice, an ARC Discovery Project on improving the design methods and technologies used in online hearings. The project brings together