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includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related to applications and applied research
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to retrieve geophysical information from satellite data. Our research drives innovation in instrumentation and retrieval algorithms, and tackle climate change, air pollution, natural hazards, and land/ocean
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transparent models. The Privacy-aware transparency decisions research group (led by Prof. Vicenç Torra) conducts research in data privacy for data to be used for machine and statistical learning. It is well
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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. The overall aim of this project is to address these challenges by: Developing new data-driven and physics-based models of battery behaviour. Designing advanced BMS algorithms for real-time monitoring and
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the research project and the division of Astronomy and Plasma Physics The successful candidate will work on developing and testing algorithms for 3D magnetic field reconstruction. The position will
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system complexity. Your work will include: Developing modular, efficient, and transparent control algorithms. Combining model predictive control with learning-based motion prediction under uncertainty
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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-fidelity qubits operations Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms About you You have a relevant PhD deegree
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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