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Field
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primarily focus on one or more of these parts. The successful candidate will develop numerical tools and/or theoretical models to model and simulate the behavior of a group of agents capable of chemical
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project combines techniques from machine learning, natural language processing (NLP), and knowledge representation to support legal scholarship and decision-making. The position entails close academic
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Deep learning models, and in particular large language
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Description The researcher will use modeled surface ocean microplastic abundances and improved sea-spray-based emission functions to represent ocean–atmosphere transfer processes. Using the GEOS-Chem global
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-frequency signals, which largely come from thermal variations at the ocean floor related to the circulation of water masses. 2. Apply fine physical models in order to better understand, characterize and
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from geomatics, spatial analysis, multi-agent modeling and simulation, and laboratory work (soil and surface formation studies; host of the Solsup platform of the EMerode service unit). General
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at the interface of materials chemistry, nanotechnology, and oncology. The project, NANOZEOXY, focuses on the design and development of nanosized zeolites as advanced carriers of oxygen and contrast agents
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the strategy to be applied for training a learning model to predict wind and precipitation conditions based on a dataset combining numerical weather prediction models and in situ observations; Collect
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writing skills in English. PhD in Biomedical Sciences, Molepular Biology, Immunology, or related fields. Specific Requirements Strong expertise in molecular and cellular biology, with hands-on experience in
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: The candidate will have to carry out research on the themes of the ERC NEMESIS Synergy project (see https://erc-nemesis.eu/ ). The aim of this project is to build an integrated computing chain based on "Discrete