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platforms like Aspen Plus. In-depth knowledge of electron microscopy, spectroscopy, and structural analysis methods for complex materials. Familiarity with REE and vanadium chemistry, oxidation states, and
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, purification and characterization of synthetic products by spectrometry and NMR, western blotting analysis, biochemical and biophysical assay development, and cell culture. 20% - Mentorship and training
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a successful candidate you will be actively involved in various research activities including laboratory and field experiments. Key Responsibilities Develop and formulate new simple and complex
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considerations in research involving human subjects. PREFERRED QUALIFICATIONS Expertise in epidemiological methods and study design. Experience with longitudinal data analysis and complex survey design. Knowledge
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systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job
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11 Nov 2025 Job Information Organisation/Company CNRS Department Institut des Systèmes Complexes de Paris Île-de-France Research Field Computer science Mathematics » Algorithms Researcher Profile
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integration Optimization and stochastic modeling methodologies Energy storage Electricity market analysis Supports multidisciplinary teams in the application of these methods and tools to complex issues in
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performing organic synthesis, purification and characterization of synthetic products by spectrometry and NMR, western blotting analysis, biochemical and biophysical assay development, and cell culture. 20
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studies on quantum materials and complex oxides, with an emphasis on microelectronics applications. In addition to experimental work, the role includes applying machine-learning and AI-based approaches
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 12 days ago
complexes. The successful candidate will develop novel graph neural network (GNN) architectures to learn dynamic information from molecular dynamics (MD) simulations of protein-protein and protein-nucleic