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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 8 days ago
Description The Odyssey team is offering a 6 month engineer position on ocean modelling within the ERC Stuod (Stochastic transport in ocean dynamics). Odyssey (for Ocean DYnamicS obSErvation analYsis) is a
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Stochastic Analysis Mission The research focus of [XXX] is centered on advancing the knowledge I the following domains: [XX] [XX] We seek outstanding candidates working in [XX] with interests in one
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structure, function, and resilience to environmental disturbances, particularly treated wastewater (TWW) irrigation. Where to apply Website http://dfa.unipd.it/servizi/amministrazione-trasparente/bandi-di
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of statistical and probabilistic methods for the analysis of complex data and systems. Research topics include distributional modelling, stochastic dependence, extreme-value phenomena, uncertainty quantification
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theories, and stochastic or diffusive effects induced by the coupling between gravity and quantum matter. Particular attention will be devoted to identifying experimentally accessible signatures capable
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 8 days ago
the Thoth project team (https://thoth.inrialpes.fr/ ) within the Inria Centre at Université Grenoble Alpes (https://www.inria.fr/en/inria-center-universite-grenoble-alpes ) to work under the supervision
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
, but are not limited to, robust and stochastic optimization, generative and foundation models, reliable and robust machine learning, uncertainty quantification, sequential decision-making, and AI systems
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‑based models (e.g., physics‑based, network‑based, agent‑based, or stochastic simulations) for analysis, experimentation, or decision support. undefined Skills & Attributes Required Advanced proficiency in
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‑related R&D programs (internships, fellowships, or full‑time roles). Familiarity with simulation‑based models (e.g., physics‑based, network‑based, agent‑based, or stochastic simulations) for analysis
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at all academic ranks, with appointments beginning in January 2027 or at a mutually agreed later date. We welcome experts in all areas of Statistics, Statistical Learning Theory and Methodology, Stochastic