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Field
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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of a blank sheet of A4 paper in a context of censorship reflects the need to recognize new forms of defiance. As speech is being monitored through different technologies and in a range of arenas from
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-based symbolic machine learning. The aim is to give the industrial widely used NewWave theory (a theory that predicts the linear shape of extreme waves) a modern twist to account for the important
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prediction of queue dissolution by combining traffic flow theory with data from roadway and AMOD sensors, nonlinear optimization of the signal plan, cooperative control of traffic signals and AMOD vehicle
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data analysis, alpha signal research, and strategy performance enhancement. While there is some overlap with the Quantitative Systematic Trader role, Quantitative Researchers typically focus more on
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project supported by an ERC Advanced Grant on the Theory of Materials for Bioelectronics. The overall goal of our research is to describe a class of organic materials able to transport ionic and electronic
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University of Eastern Finland Position ID: 3582 -PHD [#26562] Position Title: Position Type: Other Position Location: Joensuu, North Karelia 80101, Finland [map ] Subject Areas: Operator theory
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quantitative research expertise with deep trading intuition to build and refine data-driven, fully automated trading strategies. You’ll actively monitor real-time strategy performance and use market behavior and