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offering PhD positions for students with a background in data science, computer science, computational science, or a domain science with a strong focus on computational science and an interest in training
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and Data Science (MIDS) at the KU Eichstätt-Ingolstadt. The research group works at the intersection of analysis, modeling and simulation. The advertised position is partly funded by the German Research
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experimental soft matter research a supportive and enthusiastic atmosphere in-depth training in interdisciplinary soft matter science individual supervision and mentoring a PhD student mobility program with
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positions in the areas of biochemistry, structural biology, biophysics, cell biology, systems biology, and computational biology. We are looking for outstanding graduates from all over the world to join our
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on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
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Successful candidates have strong skills in computational molecular (bio)physics, structural biology and scientific computing, as well as a keen interest in interdisciplinary research and
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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scientific computing is a plus Strong interest in quantum computing and molecular simulations Willingness to work in an interdisciplinary, international team Fluent command of written and spoken English High
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semiconductor properties to the composition of lead-free double perovskites Your Profile: Master’s degree in theoretical or computational physics, chemistry, materials science, or a similar field Familiarity with
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy