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very good written and spoken English skills self-motivated, independent and responsible working style and high organizational skills ability to work in a team and willingness to integrate
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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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initiative, creativity, ability to work effectively in a team, as well as fluency of written and spoken English. What we offer: employment in accordance with the collective agreement for the public service
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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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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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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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skills, ability to communicate ideas and results effectively Independent and solution-oriented work ethic Interdisciplinary mindset and enthusiasm for teamwork Ability to work in a multi-cultural, multi
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students are supervised by a supervisory panel consisting of a panel chair, a professor from the natural sciences and a professor from information/computer/mathematical science. The DASHH graduate curriculum
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collaborating at the WindLab centred on wind physics. Our mission is to develop an improved understanding of atmospheric and wind power plant flow physics required to serve the global demand for clean and
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below 30 mK and allow the application of magnetic fields to the sample. We characterize the magnetic properties of the quantum systems using standard spectroscopic detection schemes and electron spin