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Vacancies PhD position on Dependability Driven on Device Learning Algorithms for Embedded Neuromorphic Architectures Key takeaways Edge devices that can learn autonomously while guaranteeing
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
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faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In the Reinforcement Learning Lab
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to develop your professional experience and competencies, to learn from ESA experts and to contribute to ESA activities. Technical competencies Experience with artificial intelligence and machine learning
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spoken and written. Additional experience that would be considered a plus: some experience in programming and the use of computer algebra in algebraic geometry; experience with noncommutative algebraic
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algebraic geometry, or representation theory; familiarity with programming and the use of computer algebra. Our offer A position for 18 months, with an extension to a total of four years upon successful
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-GUIDE project, we will make directed evolution guidable and, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity
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; experience with AI and machine learning methods, especially in the areas of natural language processing or graph neural networks; the ability to work independently and collaboratively in an interdisciplinary
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, Philosophy, Educational Sciences, and Health Sciences. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging
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We have openings for two Assistant Professors to strengthen our position in the following fields: Machine Learning / Pattern Recognition Machine Learning / Generative AI Machine Learning / Pattern