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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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Do you want to contribute to groundbreaking research in the intersection of battery systems and data-driven optimization? This is an exciting opportunity for a postdoctoral position at the Division
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely connected
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; developing and optimizing doping protocols for conjugated polymers and other organic semiconductors; correlating materials chemistry and microstructure with electronic performance; implementing the resulting
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implemented globally. The research includes optimization of the electrochemical processes for mercury removal as well as safe and efficient retrieval of the removed mercury and regeneration of electrodes
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for industrial application. You will develop materials and processes enabling this technique to be scaled up and implemented globally. The research includes optimization of the electrochemical processes
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engineering. The work involves simulations for quantum error correction and mid-circuit operations, and will require both low-level optimization skills (e.g., SIMD, GPU, FPGA) and an understanding of quantum
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international professional network between researchers and industry associated with the WASP. Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized
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one of the most critical challenges in modern energy systems, maintaining stability in an increasingly converter-dominated power network. The project will be carried out in close collaboration with