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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 20 days ago
at the University of Oldenburg and involving national and international partner institutions. As a diverse and international team of scientists from biology, physics, chemistry, computer sciences and social sciences
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and technologies. The institute employs an average of 500 people from over 40 nations and, in addition to its scientific tasks, is dedicated to promoting young scientists and engineers. Further
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compilation, optimization and error mitigation collaborate with theoretical computer scientists on developing noise-aware quantum programming paradigms Your Profile: Master in physics, computer science
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methods like ZX-calculus) towards description of quantum noise employ such extended methods for quantum circuit compilation, optimization and error mitigation collaborate with theoretical computer
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware
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neuromorphic hardware, this project will push into next-generation analog circuits and memristive devices, in collaboration with PGI-14. The goal is to train a system that leverages the intrinsic non-linear
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electronic complementary metal oxide semiconductor digital circuits with the help of artificial intelligence. Unleash your potential in an inspiring environment focused on research and development
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integrated circuit design, testing and simulation using Cadence is a plus Knowledge of evolutionary optimization methods is a plus Very good communication skills in English, both spoken and written. PGI-15
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electronics, or related areas. • Familiarity with integrated circuit design, signal processing, or multiphysics simulations is advantageous. • Interest in cross-disciplinary research at the interface of sensor
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discipline boundaries and abstraction levels is a must. Knowledge in integrated circuit design, testing and simulation using Cadence is a plus. Knowledge of digital neuromorphic hardware and sensors is a plus