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some background in one or more of the following areas: Mathematical Optimization / Operations Research Reinforcement Learning, Machine Learning, and/or Multi-agent systems Game Theory Algorithms
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engineering, with a strong willingness to learn the complementary skill set. Experience in collaborative research environments. Excellent communication and teamwork skills. A proactive attitude towards learning
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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applications. Teach and supervise BSc and MSc student projects. The research activity will be carried out within the framework of the Center of Excellence – IDUN. In IDUN, our motto is ‘bringing science to life
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processing and hybrid BCI design Machine learning (ML) Bioinspired control systems Neuroplasticity and motor recovery Real-time control of soft exoskeletons Your Role As a PhD candidate, you will: Develop and
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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models, and reinforcement learning (RL), which is data-driven, are two powerful control techniques. MPC techniques are well-established, while RL techniques are gaining popularity due to increasingly
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leaders via our educational activities and opportunities for lifelong learning. Complex challenges call for joint action, and therefore our strategy focuses on strengthening current and starting new
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opportunities for lifelong learning. Complex challenges call for joint action, and therefore our strategy focuses on strengthening current and starting new partnerships with other sciences, the business community
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Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in