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-Computer Interaction, Information Science, Computer Science, Cognitive Science, Design, Sociology, Psychology, Education, or a related field Demonstrated expertise in mixed-methods research, including
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. We will develop a posteriori estimation tools to obtain error indicators that will guide mesh adaptation. These indicators must be specifically designed to account for the anisotropy of the field. Our
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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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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 | 10 days 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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QUALIFICATIONS: • PhD in Electrical and Computer Engineering, Mechanical Engineering, Physics, or a closely related field. • Demonstrated expertise in MEMS/NEMS design and modeling, including finite element
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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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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours 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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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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evaluating the effectiveness of various recharge methods. A specific focus of this component is understanding subsurface structures that can facilitate focused recharge (e.g. sinkholes, losing/gaining streams