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engineering Willingness to work in laboratory and cleanroom environments Ideally, initial experience in a technical or scientific environment (e.g. cleanroom, laboratory) Knowledge of solid state physics and/or
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Jülich Participation in the development of the institute Your Profile: Sucessfully completed scientific university degree (Master) in the fields of chemical engineering, technical chemistry, physical
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the structure and function of matter, from the smallest particles of the universe to the building blocks of life. In this way, DESY contributes to solving the major questions and urgent challenges facing science
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Engineering and Information Technology Department of Mechanical Engineering Department of Physics Department of Chemistry and Biosciences Course language English Financial support Yes Structured research and
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susceptible steel structures. Thus, the candidate will develop reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be
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Max Planck Institute for the Physics of Complex Systems • | Dresden, Sachsen | Germany | about 4 hours ago
University, Prague/CZ Institute of Low Temperature and Structure Research, Wroclaw/PL University of Wroclaw/PL Wroclaw University of Science and Technology/PL Teaching language English Languages 100% English
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Degree German doctoral degrees covered by LogDynamics: "Dr-Ing": Doctor of Engineering "Dr rer nat": Doctor of Natural Science "Dr rer pol": Doctor of Economics "Dr jur": Doctor of Laws Course
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researchers from around the world. We offer a wide range of career opportunities in science, technology, and administration. Organic light-emitting diodes (OLEDs) are a popular class of semiconductor devices
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we