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Python or R A willingness to learn and apply machine learning approaches We offer A versatile and challenging job in a vibrant and world-class research environment operating at an international level
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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background in machine learning, including Natural Language Processing. You have excellent coding skills in Python; hands-on experience in deep learning frameworks such as PyTorch or Tensorflow is a plus You
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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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of predictive models for energy demand and production. These models will leverage techniques such as time series analysis and machine learning and will be integrated into a digital twin platform. The aim is to
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, criterion handling and machine learning. Topic The main research objective is to contribute to the development of responsible AI, with a strong focus on trust and confidence handling when dealing with data
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. You have a good knowledge of Python and machine learning. You have an excellent knowledge of English. Your research qualities are in line with the faculty and university research policies . You act with
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-type specific samples, state-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches
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are looking for a m/f/x Doctoral fellow YOUR JOB You conduct doctoral research in the area of Augmenting Learning Environments Using Generative AI and Neuroadaptive Systems, with the aim to obtain a PhD after