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proficient in ROS/ROS2, Python and/or C++/C# Knowledge and/or experience within one or more of the fields of acoustic sensing, hydrodynamics, and machine learning is a plus. You have strong communication
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system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models and machine
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and
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was established to create value for and with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make a positive difference to society 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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needed to achieve these temperatures, the control cables connecting to the qubits are often more than 2 meters long. At the same time, a quantum computer powerful enough to solve problems beyond the reach
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decision-making. Collaborate with international partners and contribute to joint research activities. Teach and co-supervise students at different levels in courses and associated projects. Publish and
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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circular plastics economy. Learn more about the project at https://inano.au.dk/about/research-centers-and-projects/enzync . If you are applying from abroad, you may find useful information on working in
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. Experience in quantum nanophotonics, quantum photonic devices, nanoscience, nanotechnology, and quantum dots is welcomed. Learn more about the project here: nikaakopian.org/multiqubit . The project is