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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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Nanotechnology or similar Knowledge andprofessional experience: Knowledge of machine learning and active learning in material science. Experience working in multidisciplinary environment. Personal Competences
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characterization, and integration of machine learning to correlate synthesis conditions with functional performance. The goal is to establish predictive synthesis strategies for oxygen vacancy control, with
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Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Personal Competences: Demonstrated competitive ability in using DFT simulations, and machine learning techniques and DFT. Demonstrated strong coding skills and a passion for UX/UI design. Summary
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models · Collate and store accurate records using paper and computer-based systems and the preparation of data for inclusion in lab books, presentations and publications. Maintain a hardcopy or electronic