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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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/2025.03.02.641062 Your Profile The successful applicant should hold a master's degree or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 22 hours ago
Dresden University of Technology (TUD) Course location Dresden In cooperation with Dresden University of Technology (TUD) Teaching language English Languages The programme is conducted in English. Full-time
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented
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(e.g. between Christmas and New Year) Further development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking
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to work in a team and in a research network • Computer programming experience • Knowledge in electronics • Experience in the field of optics and quantum optics is desirable We offer: • A truly unique
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, computational model development, data processing, and code implementation in close cooperation with scientists. The position is limited to 3 years. Equal opportunity is an important part of our personnel policy
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data
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Description The Karlsruhe Institute of Technology (KIT) and the University of Stuttgart offer within the German Research Council (DFG)-funded Research Training Group (RTG) 3076 “Sustainable