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and tomographic radar capabilities. Our team is responsible for the algorithms which derive the biomass data product. The post-doc project is about extending the biomass algorithm to also include data
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to develop complement/augment classical CFD methods with quantum algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we
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the algorithmic capabilities of intelligent systems, reducing their computational costs, and bridging the gap between hardware and algorithm design. Duties and responsibilities The appointment as a postdoctoral
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tree. In fact, the problem being NP-hard, a handful of aircraft is enough to make it unsolvable in polynomial time. The work requires theoretical studies on the state of the art, together with algorithm
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We are seeking a postdoc to co-design efficient and realistic simulation algorithms for noisy quantum circuits in superconducting hardware, combining quantum modeling with hardware-aware performance
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-terrestrial networks, and the performance evaluation of these solutions in challenging IoT scenarios. The position involves both theoretical and experimental research, including algorithm design, simulation
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expertise in existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will contribute to building a
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including
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in conducting research on AI, algorithmic governance, automation, digitalisation and the implications for the public sector Experience applying analytical and methodological research approaches
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Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms Who we are looking for The following requirements are mandatory: A