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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
collaborate with colleagues from multiple universities across the Research Triangle, the United States, and even the world. Position Summary The Research Assistant (RA) will support advanced research in
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applications to fill multiple faculty positions in the field of quantum information science, broadly defined. Faculty will join the newly established Institute for Quantum and Information Sciences
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applications to fill multiple faculty positions in the field of quantum information science, broadly defined. Faculty will join the newly established Institute for Quantum and Information Sciences
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well as in the design of machine learning algorithms (ANN, SVM, Decision Tree, and Random Forest) applied to healthcare, will be particularly valued. Proficiency in programming tools (Matlab) and statistical
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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to the body of knowledge by enhancing the safety, relia- bility, and efficiency of automated vehicles by developing a collaborative multimodal perception system. This system leverages data from multiple sources
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2 Sep 2025 Job Information Organisation/Company CNRS Department Maison de la Simulation Research Field Computer science Mathematics » Algorithms Researcher Profile Recognised Researcher (R2) Country
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for Multi-Agent Decision-Making, https://oceanerc.com ). This timely project will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making
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multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address fundamental scientific challenges