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stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic mechanisms are needed to be derived
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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large quantities of data to gain a greater understanding of our systems and develop data analytics and artificial intelligence algorithms. You will be actively engaged in the research and development
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applications for a Research Associate / Postdoctoral Associate position, in the area of Quantum Computing Security. The candidate is expected to do cutting-edge research in multiple of the following areas
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" setting [4], where the benchmark is the optimal online algorithm rather than the expected maximum, making the competition more dynamic. - Study settings where multiple items are allocated to buyers, such as
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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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Scalable Inference: Develop new algorithms for scalable uncertainty quantification (UQ) and Bayesian inference and apply them to challenging simulation problems. The goal is to produce robust, validated
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machine learning algorithms for application to sonar and underwater acoustics, as well as the accompanying data analysis to effectively characterize their performance in the Advanced Technology Laboratory
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courses on data mining, algorithmic bias, data ethics, and critical data studies. Intermediate and upper level courses could include modeling and simulation, data analytics for spatial analysis, geographic
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, prove the convergence and stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic