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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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guidance, navigation, and control (GNC) systems. The successful candidate will develop and validate Bayesian and non-Gaussian estimation algorithms, data assimilation methods, and tracking frameworks
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evolutionary). The project aims to approximate a Boltzmann distribution associated with an objective function that is difficult to optimize in order to solve complex optimization problems. This probabilistic
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 5 hours ago
. The project will initially focus on the Grenoble metropolitan area, with the objective of developing methods that are scalable and transferable to other regions at the international level. This position is part
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of advanced modelling and machine learning methods, and may involve the following areas: Dimensionality reduction. Data-driven methods for estimating dynamical models Data-driven methods for estimating
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We are seeking to recruit a 2-year postdoctoral researcher within Human-Computer Interaction to work on the interdisciplinary project DARES: Data Quality for Responsible AI in Energy Systems funded
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that makes that reuse possible at scale — not just once, but sustainably, across the research community? The Davis and Krishnan labs work at the intersection of these questions. We develop ML/AI methods and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
medium. Methods of investigation may include analyses of archival multi-wavelength observations from space- and ground-based facilities, as well as new observations and analyses. Additional interests
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to develop an innovative model to estimate the direct and indirect costs of urbanization based on urban morphology (compact or sprawling). The candidate will analyze real case studies, integrate variables
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tractability, decomposition methods), learning-enhanced approximations (e.g., embedding-based representations of complex interactions, passenger flow estimation using generative techniques), and artificial