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the subject of Machine Elements, where the research is primarily focused on tribology and its applications. The research group currently consists of about 40 researchers and doctoral students and is one
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Engineering, Mechatronics, or Robotics, with a heavy emphasis on dynamic system theory, or a closely related discipline. Strong academic background in applied intelligent control techniques, machine learning
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expertise in programming (C++, Python), computer architectures and Deep Learning (PyTorch, TensorFlow). Exceptional international candidates may be eligible for a fee waiver (read the following section
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research team, you get the chance to develop in tribology, work interdisciplinary and conduct research in close collaboration with industry. You will be working in the subject of Machine Elements, where
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Dovrolis: PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity. ICML 2025 Job requirements Master’s degree in: Computer Science, Machine Learning
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environment in this research group that is actively involved in scientific research at the highest international level in different domains such as conceptual modelling, model-driven engineering, smart learning
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of machine learning, and/or ecological modelling. Excellent oral and written English language skills. Strong collaborative skills, team spirit and the ability to also work independently. Experience with field
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PixHawk Autopilot, Arduino boards, Raspberry Pi - or equivalent Experience with ROS/ROS2 Experience with programming languages like Matlab, Python, C++ Familiarity with machine learning and/or deep learning
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to the different situations and the benefits or costs that come from the group dynamics. We will moreover compare different types of collective problems (cooperation, coordination…) and investigate if and how global
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Science, Machine Learning, Finance, FinTech, Economics, or a related field. Candidates should demonstrate knowledge of Large Language Models, generative AI, and machine learning, with interest in financial