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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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precision Mechatronics systems and algorithms. Ability to develop kinematic and/or dynamic analysis of Mechanical/Robotic systems. Ability to implement control and kinematics with hardware-in-the–loop
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scheduling in shared workspaces - Shared autonomy and predictive learning - Human-robot teaming in distributed decision-making Sensing and perception - Collaborative perception and localization - Learning
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Efficient Wireless Communication Solutions, IoT verticals, Unmanned Aerial Vehicles, Integrated Satellite-Space-Terrestrial Networks, Quantum Communications and Key Distribution, Spectrum Management and
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control
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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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algorithms model major sources of experimental error for control theory or co-design methods Previous works can be found under the bibliographies of Dr. Felix Motzoi and and Dr. Matthias Müller: https
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institutions and governmental practices to ensure that support meets local needs. Structural challenges such as resource distribution, access to finance, corruption, multilevel governance systems and
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of Europe’s ‘green transition’ to clean energy. You will work on cutting-edge research tasks, with objectives including • new algorithms and strategies to improve autonomous Airborne Wind Energy (AWE) operation