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the fields of chemical engineering, technical chemistry, organic chemistry or a comparable discipline Knowledge of hydrogen and energy research is an advantage Independent and self-motivated way of working
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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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Description In the research group Dependable and Autonomous Cyber-physical Systems (DACS) on Institute for Software and Systems Engineering (ISSE) at Clausthal University of Technology has
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engineering with TensorFlow or similar frameworks Ability to develop Spiking Neural Networks from scratch, including training and quantization Optimize and benchmark applications and models for neuromorphic
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technology The ability to quickly familiarize yourself with new technical and scientific contexts Highly motivated and having a clear focus on producing high-quality scientific publications in peer-reviewed
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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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( e.g., "Diplom", DEA) in exceptional circumstances: excellent BSc The first step in the process of application for admission to the PhD programme at the Department of Physics and Electrical Engineering
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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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grades in the field of mechanical engineering, material science, physics, computational science or similar, preferably with a specialization in the field of theory and/or simulation Strong understanding
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, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org/research