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are not fully integrated into the exploration of subsurface exploration workflows due to data resolution limitations and challenges in modeling. This knowledge gap limits our understanding of resource
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underground mines and areas prone to rockfall. The work covers scene understanding with foundation models, navigation, and coordinated decisions within the robot team when communication is limited. Subject
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learning. The group studies how language models acquire, use, and communicate information, and how these systems can be evaluated and deployed responsibly in consequential settings. We are particularly
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models for the growth of polycyclic aromatic hydrocarbons (PAHs). Existing models will be updated with more accurate kinetic parameters to improve the understanding of the key mechanisms governing PAH
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. The work covers scene understanding with foundation models, navigation, and coordinated decisions within the robot team when communication is limited. Subject description Robotics and artificial intelligence
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? To address these questions, the applicant will combine state-of-the-art emission models for photoionized, photodissociated, and shocked gas (CLOUDY, Meudon PDR, and Paris-Durham codes) to disentangle
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. The position will involve working with large regional and global datasets, developing and applying quantitative models, evaluating environmental and productivity outcomes, and supporting the design and analysis
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . Position Overview We are seeking a highly motivated Research Fellow to join our research team focusing
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of statistical and probabilistic methods for the analysis of complex data and systems. Research topics include distributional modelling, stochastic dependence, extreme-value phenomena, uncertainty quantification
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with large regional and global datasets, developing and applying quantitative models, evaluating environmental and productivity outcomes, and supporting the design and analysis of case studies