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mesoscopic properties of active units within a collective to its macroscopic behavior based on simulation data. Another possibility is to equip active units with learning capabilities or adaptive interactions
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and X-ray experiments to explore the structural, electronic, and magnetic properties of quantum magnets Developing an understanding of the underlying magnetic processes through complex data analysis and
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Voigtlaender) is part of the Mathematical Institute for Machine Learning and Data Science (MIDS) at the KU Eichstätt-Ingolstadt and is funded by the High-Tech Agenda of Bavaria. The advertised position is funded
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and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among others of the following tasks: Investigate and design
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and Geography Geoscience Geography Programmes Faculty of Mathematics and Computer Science Mathematical Sciences (SMS) Computer Science (PCS) Data Science (PDS) Thematic programme Environmental
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doctoral programme provides an outstanding environment for young scientists to tackle grand societal, scientific, and industrial challenges in the fields of energy, health, matter, and data science. The
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Course location Heidelberg Description/content The Graduate Academy As a coordinating hub for meta-disciplinary skills training, career orientation and information services, the Graduate Academy
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For the winter semester: 15 October - 28 February More information on application periods Please find more details on this website . Combined Master's degree / PhD programme No Joint degree / double degree
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the Department of Plant Biochemistry at the Center for Plant Molecular Biology (ZMBP), University of Tübingen. The position is available from January 2027 and is initially funded for three years, with
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or interest in this position. General information and research topics of the Maaß-group can be found at www.maass.nu. The position is suitable for disabled persons. Disabled applicants will be given preference