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Field
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research group of Prof Emily Shuckburgh, as well as being part of the Centre for Landscape Regeneration (CLR). The CLR is an ambitious programme of research that aims to provide the knowledge and tools
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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optimization techniques. You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax) and proven ability of CUDA and Python programming. Knowledge of, or prior experience with, optimizing
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improve overall task efficiency. Topics may include autonomous mission planning, resource-aware scheduling, multi-drone coordination, optimization-based decision-making, and integration of robotic
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: “Optimizing microwave plasma-based reduction of metal oxides” under the supervision of Prof. von Keudell, Chair for Experimental Physics – Reactive Plasmas at the Faculty of Physics and Astronomy, Ruhr
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algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems
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. The techniques used will include Laser Doppler Vibrometry (LDV) and Air Coupled (AC) ultrasound detection. The candidate will design optimized setups for (i) vibration excitation by an impactor or ultrasonic
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publications, participating in conferences). Required skills: • Solid knowledge of heterogeneous catalysis, including the synthesis, physicochemical characterisation and catalytic evaluation of composite
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects