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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
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platforms and field validation. Key Responsibilities Develop advanced methods in robust and adaptive control , state estimation , and motion planning Design and implement control and perception algorithms for
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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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-propagation mechanisms. Develop capacity-estimation, demand-forecasting, performance-benchmarking, and what-if assessment methods to support planning and operational decision-making. Investigate the
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representation 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
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University of California, San Diego | Estancia de San Diego, Guanajuato | Mexico | about 22 hours ago
-order predictions together with heterogeneous observational data. • Integrate data driven methods into a framework for uncertainty-aware ocean state estimation. • Apply and validate the framework using
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learning–based post-processing methods to enhance forecast skill for convective hazards. • Perform spatio-temporal data analytics on weather and/or hydrological fields. • Collaborate closely with
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volume estimation, navigation, decision-making, and control modules within a simulation-based validation framework. Develop methods to estimate the safe operational capacity for drone operations under
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clinical epidemiology, and working with methods like random forest and targeted learning, the candidate will contribute to the development of interpretable survival models and doubly robust estimation
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, quantum sensing or quantum parameter estimation. Experience with convex or semidefinite optimisation, variational methods, or computational complexity. Proficiency in relevant scientific programming