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to facilitate communication with technical staff and administrative services • Basic knowledge of mechanical engineering or experience with fiber spinning equipment is an advantage • Practical, hands-on skills
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nanoindentation, for generating their own data sets Your Profile: A completed university degree (Master or equivalent) with excellent grades in the field of data science, material science, mechanical engineering
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(master’s or equivalent) with excellent grades in the field of data science, material science, mechanical engineering, physics, or similar, with a strong machine learning or simulation background In-depth
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was established in 2019 with our partner institute, the Nagoya Institute of Technology, Japan, in order to better understand lead-free perovskite materials for photo-electro-mechanical energy conversion systems
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of Economics and Management Faculty of Mathematics and Natural Sciences Faculty of Organic Agricultural Sciences Faculty of Civil and Environmental Engineering Faculty of Mechanical Engineering Faculty
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Lüneburg) and supported by Dr.‑Ing. Frederic Bock (Hereon). The objective is to combine computer simulations and machine leaning models to extend their compatibility with problems from mechanical engineering
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of Technology. At each location we bring together more than 150 staff members. In ScaDS.AI, various research topics are being worked on within the framework of a graduate school on the fundamentals and
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at other institutions. The project includes the following secondments: three months at Anhalt University of Applied Science (Dirk Benndorf’s lab) in Köthen, Germany and two months at the de.NBI offices
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to cancer, metabolic disorders, and infections. As part of this position, you will have the opportunity to contribute to cutting-edge research aimed at understanding microbiome-driven mechanisms and
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investigating degradation mechanisms within the framework of green energy conversion and climate change. The open position aims to understand catalyst stability at the nanoscale during electrochemical processes