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energy storage and other fields. The overall aim of the PhD is to understand the process of nanowire growth by studying its sequential reactions (alloy formation, crystal nucleation, layer growth, etc
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dedicated to autonomous experimentation, with the opportunity to explore other cutting-edge topics such as machine learning and methodology for accelerated materials discovery. Additionally, the hired
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" (KESADIAS) [Reference CNS2024-154608]. Where to apply Website https://jobs.materials.imdea.org/apply/form?id=60453 Requirements Specific Requirements PhD in computational physics, computational chemistry
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highly desirable. The successful candidate must demonstrate strong leadership, communication, and teamwork skills to foster a collaborative research environment. Experience in supervising PhD students and
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must demonstrate strong leadership, communication, and teamwork skills to foster a collaborative research environment. Experience in supervising PhD students and early-career researchers, as
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for recent master's graduates (or soon to graduate) in fields related to informatics, masters in AI, material science and engineering, or related disciplines with excellent academic credentials pursuing a PhD