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: (i) the rarity of extreme events, which renders classical statistics inadequate; (ii) the uncertainty inherent in cascading effects; and (iii) the lack of confrontation between numerical models and
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determinations for the different models, including sample preparation and chromatographic determinations by GC-MS and other techniques Preprocess chromatographic fingerprinting data and to develop and validate
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 11 hours ago
carbon-cycle modeling. The project will build a unified modeling framework that uses GEDI LiDAR and Landsat/HLS data to train deep learning models capable of predicting forest structure variables such as
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Project summary: Project examines whether Large Language Models (LLMs) embed systematic political ideologies that influence their financial judgements. Extends a novel auditing framework to measure
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of determinacy theory, forcing techniques, inner model theory and large cardinals. Where to apply E-mail gsargsyan@impan.pl Requirements Research FieldMathematicsEducation LevelPhD or equivalent LevelGood
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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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Institut de Chimie des Substances Naturelles (ICSN), CNRS, UPR 2301 | Gif sur Yvette, le de France | France | about 23 hours ago
human cell lines, including breast cancer models, as well as in the eukaryotic model Saccharomyces cerevisiae. First, the protein network of the ferredoxins will be mapped using proteomics, genomics, and
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on the modelling of transmission dynamics and risk assessment of mosquito-borne arboviruses with the potential to invade the EU. Addressing this challenge requires an interdisciplinary approach, combining
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of the project MESSENGER: « Can rock-powered Microbial EcoSyStEms provide valuable iNsiGhts into early life and its emERgence? » funded by the PEPR ORIGINS (https://pepr-origins.fr/en/ ) and integration
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of this thesis focus on several key areas: - Detection and modeling of node mobility: Supervised learning models will be developed to identify mobility patterns based on radio indicators such as RSSI, SNR, and