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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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, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain
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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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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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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and
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passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in
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include writing scientific manuscripts, presenting project outcomes, and to supervise students at basic and advanced level. The research project will be coordinated by Prof. Rickard Ignell at SLU Department
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for scientific purposes. The postdoc will work with Prof. Daniel Metcalfe (Umeå University, Sweden) and Dr. David Bartholomew (Botanic Gardens Conservation International, Brazil), and collaborators within
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including, among others, Prof. Maria Riveiro. You will focus on developing and evaluating explanations from AI systems. Your work includes teaching or other departmental duties, up to a maximum of 20% of full