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perfusion and mechanical stimulation in tumor tissues to investigate their poromechanical properties and optimize molecular transport within explants. The successful candidate will be involved in: - Designing
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) designs and/or studies materials with novel properties. This requires expertise in material synthesis, advanced characterization, physical property studies, as well as modeling and theoretical description
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controlled group experimental tasks. The candidate will participate in the design, implementation, and analysis of behavioral experiments combined with non-invasive neuroimaging measurements, with
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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validation tests of experimental results related to developed prototypes. Designing conversational solutions and for the assessment of conversational solutions after having worked on LLM's. - ISOL, M. Penco
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of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
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low-carbon power-generating reactors based on laser fusion. In France, the Taranis project, selected in March 2024 as part of the France 2030 plan and led by the startup GenF, brings together a national
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. Jose Moran-Mirabal's laboratory at McMaster University (Canada), internationally recognized for advanced biomaterials and hydrogel engineering. The successful candidate will participate in the design and
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archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming