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will focus on: Bibliographic review, Report and scientific publications. organizing workshop courses Skills required for the position: The candidate must have: PHD with skills in one of the following
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for the position: The candidate must have: PHD with skills in one of the following fields: history, philosophy, anthropology, sociology, psychology Rigor / motivation, Good communication skills, Teamwork
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interdisciplinary teams that involve experimentalists and modelers Criteria of the candidates: PhD in Chemical/Mechanical Engineering, Applied Chemistry, Applied Mathematics, Physics, or related disciplines, with
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synthesis and characterization with a PhD and demonstrated experience in Materials Science, Materials Chemistry, Inorganic chemistry, catalysis, and related disciplines. The candidate should also have
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synthesis will involve wet chemistry and other well-established solid-state methods. Required qualifications: The candidate must hold a PhD degree in Materials Science, Materials Chemistry, Inorganic
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at scientific meetings and conferences. Co-supervise ungraduated, graduate and PhD students Participate in developing research proposals and programs in the area of collaboration with multidisciplinary
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libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications and machine learning. Integrate and benchmark the GINGKO library, a sparse solver
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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experimental results. Ability to work in interdisciplinary teams that involve experimentalists and modelers. Criteria of candidates: PhD in Chemical/Mechanical Engineering, Energy, Applied Chemistry, Applied
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candidate must have as well a multidisciplinary scientific profile: PhD degree in materials science, chemical engineering, chemical Processes or another suitable engineering discipline. Knowledge about