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Energy Environment Water Research Centre (EEWRC) The Climate and Atmosphere Research Centre (CARE-C) The Science and Technology Driven Policy and Innovation Research Centre (STeDI-RC) Considerable cross
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
. The candidate may help develop a projection layer that connects predicted geospatial features and metrics to an open-source large language model (LLM), enabling natural-language queries over forest conditions and
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Advanced Systems-Modelling and Optimisation in Materials Science and Engineering School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Mahdi Mahfouf Application
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and remote sensing datasets for model validation. Develop new functionalities in the Community Land Model (CLM) within CESM. Conduct model simulations to investigate how the tropical atmosphere responds
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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– development of scenarios for the network analysis. --- Model development – development of a model that enables the analysis of the impacts of adding sensing capabilities. --- Model implementation
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of thermal degradation. This research has enabled the development of effective kinetic models, based on parallel or sequential reactions. However, the actual operating conditions of pellet stoves
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), multimodal vision and language models, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate
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LIST? Check our website: https://www.list.lu/ How will you contribute? The Post-Doc researcher will develop, implement, and apply advanced ways in inverting a radiative transfer model for forest trait
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conditions. Expected outcomes of this thesis include precise models for mobility detection and radio parameter adaptation, experimentally validated intelligent ADR and handover mechanisms, efficient learning