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Field
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/Qualifications Research experience in geography and the circular bioeconomy in France. Knowledge of public policies regarding waste and organic matter management. Knowledge of agricultural practices in rural areas
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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materials. Materials for aerospace or space applications. Knowledge of experimental data analysis and scientific programming/software would also be considered an asset. Specific Requirements Key
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academic incentives (Balafoutas et al., 2025), scarce evidence, insufficient replication (Finger et al., 2023), practices’ heterogeneity (Arpinon, 2025), lack of precise knowledge (Arpinon & Espinosa, 2023
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transversal skills : Expertise in polymer processing technologies including 3D printing Skills in microstructural analysis and mechanical modelling Knowledge in plant biology and/or plant biomechanics Internal
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have a solid understanding of the different types of superstring models and associated supergravity theories. Knowledge of mathematical concepts useful for the project (differential geometry, exceptional
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Information Eligibility criteria We are looking for candidates with knowledge of Python programming, metabolic modeling, and multi-omics data analysis, as well as strong teamwork and communication skills
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projects related to gene therapy in mouse model for human inner ear defect. These projects will require strong interest in sensory systems with knowledge and training in neuroscience. This includes gene
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Skills and Qualifications • PhD in Chemistry, Physicochemistry of Polymer Materials, or a related field. • Strong experience in polymer characterization. Knowledge of bio-based materials is a plus but not
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expertise in FRET/FLIM microscopy. Knowledge of biosensors or high-resolution microscopy (Airyscan, dSTORM, or SRRF) would be a plus. - Design and carry out experiments, from sample preparation to data