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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
methods or machine learning is an advantage # Strong communication skills and a collaborative approach to working with internal and external partners # Independent, structured and solution-oriented way
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | 2 months ago
, fostering the research necessary to maintain global competitiveness in innovative technologies. The learning objectives for this project are: • Developing innovative approaches that effectively convert REE/CM